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Amplifiers with feedback : electronic engineering : presentation transcript

Description

This open educational resource was released through the Higher Education Academy Engineering Subject Centre Open Engineering Resources Pilot project. The project was funded by HEFCE and the JISC/HE Academy UKOER programme.Subjects

input | output | voltage | voltage series feedback | configuration | series feedback | resistance | university of wales | feedback | gain | engsc | newportunioer | bandwidth | electronics | oer | beng | current shunt feedback | voltage shunt feedback | shunt feedback | newport | ukoer | current | current series feedback | engscoer | foundation degree | amplifiers | 2009 | amplifiers with feedback | electronic engineering | engineering | hn | Engineering | H000License

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See all metadata6.832 Underactuated Robotics (MIT) 6.832 Underactuated Robotics (MIT)

Description

Includes audio/video content: AV lectures. Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which involve a loss of instantaneous control authority. Controlling nonlinear systems without complete control authority requires methods that can reason about and exploit the natural dynamics of our machines. This course discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods. Topics include nonlinear dynamics of passive robots (walkers, swimmers, flyers), motion planning, partial feedback linearization, energy-shaping control, analytical optimal control, reinforcement learning/a Includes audio/video content: AV lectures. Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which involve a loss of instantaneous control authority. Controlling nonlinear systems without complete control authority requires methods that can reason about and exploit the natural dynamics of our machines. This course discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods. Topics include nonlinear dynamics of passive robots (walkers, swimmers, flyers), motion planning, partial feedback linearization, energy-shaping control, analytical optimal control, reinforcement learning/aSubjects

underactuated robotics | underactuated robotics | actuated systems | actuated systems | nonlinear dynamics | nonlinear dynamics | simple pendulum | simple pendulum | optimal control | optimal control | double integrator | double integrator | quadratic regulator | quadratic regulator | Hamilton-Jacobi-Bellman sufficiency | Hamilton-Jacobi-Bellman sufficiency | minimum time control | minimum time control | acrobot | acrobot | cart-pole | cart-pole | partial feedback linearization | partial feedback linearization | energy shaping | energy shaping | policy search | policy search | open-loop optimal control | open-loop optimal control | trajectory stabilization | trajectory stabilization | iterative linear quadratic regulator | iterative linear quadratic regulator | differential dynamic programming | differential dynamic programming | walking models | walking models | rimless wheel | rimless wheel | compass gait | compass gait | kneed compass gait | kneed compass gait | feedback control | feedback control | running models | running models | spring-loaded inverted pendulum | spring-loaded inverted pendulum | Raibert hoppers | Raibert hoppers | motion planning | motion planning | randomized motion planning | randomized motion planning | rapidly-exploring randomized trees | rapidly-exploring randomized trees | probabilistic road maps | probabilistic road maps | feedback motion planning | feedback motion planning | planning with funnels | planning with funnels | linear quadratic regulator | linear quadratic regulator | function approximation | function approximation | state distribution dynamics | state distribution dynamics | state estimation | state estimation | stochastic optimal control | stochastic optimal control | aircraft | aircraft | swimming | swimming | flapping flight | flapping flight | randomized policy gradient | randomized policy gradient | model-free value methods | model-free value methods | temporarl difference learning | temporarl difference learning | Q-learning | Q-learning | actor-critic methods | actor-critic methodsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata16.30 Feedback Control Systems (MIT) 16.30 Feedback Control Systems (MIT)

Description

This course will teach fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, you should be able to design controllers using state-space methods and evaluate whether these controllers are robust to some types of modeling errors and nonlinearities. You will learn to: Design controllers using state-space methods and analyze using classical tools. Understand impact of implementation issues (nonlinearity, delay). Indicate the robustness of your control design. Linearize a nonlinear system, and analyze stability. This course will teach fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, you should be able to design controllers using state-space methods and evaluate whether these controllers are robust to some types of modeling errors and nonlinearities. You will learn to: Design controllers using state-space methods and analyze using classical tools. Understand impact of implementation issues (nonlinearity, delay). Indicate the robustness of your control design. Linearize a nonlinear system, and analyze stability.Subjects

control design | control design | control analysis | control analysis | state-space methods | state-space methods | linear systems | linear systems | estimation filters | estimation filters | dynamic output feedback | dynamic output feedback | full state feedback | full state feedback | state estimation | state estimation | output feedback | output feedback | nonlinear analysis | nonlinear analysis | model uncertainty | model uncertainty | robustness | robustnessLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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6.241 examines linear, discrete- and continuous-time, and multi-input-output systems in control and related areas. Least squares and matrix perturbation problems are considered. Topics covered include: state-space models, modes, stability, controllability, observability, transfer function matrices, poles and zeros, minimality, internal stability of interconnected systems, feedback compensators, state feedback, optimal regulation, observers, observer-based compensators, measures of control performance, and robustness issues using singular values of transfer functions. Nonlinear systems are also introduced. 6.241 examines linear, discrete- and continuous-time, and multi-input-output systems in control and related areas. Least squares and matrix perturbation problems are considered. Topics covered include: state-space models, modes, stability, controllability, observability, transfer function matrices, poles and zeros, minimality, internal stability of interconnected systems, feedback compensators, state feedback, optimal regulation, observers, observer-based compensators, measures of control performance, and robustness issues using singular values of transfer functions. Nonlinear systems are also introduced.Subjects

control | control | linear | linear | discrete | discrete | continuous-time | continuous-time | multi-input-output | multi-input-output | least squares | least squares | matrix perturbation | matrix perturbation | state-space models | stability | controllability | observability | transfer function matrices | poles | state-space models | stability | controllability | observability | transfer function matrices | poles | zeros | zeros | minimality | minimality | feedback | feedback | compensators | compensators | state feedback | state feedback | optimal regulation | optimal regulation | observers | transfer functions | observers | transfer functions | nonlinear systems | nonlinear systems | linear systems | linear systemsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata16.31 Feedback Control Systems (MIT) 16.31 Feedback Control Systems (MIT)

Description

The goal of this subject is to teach the fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, students should be able to design controllers using state-space methods and evaluate whether these controllers are "robust," that is, if they are likely to work well in practice. The goal of this subject is to teach the fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, students should be able to design controllers using state-space methods and evaluate whether these controllers are "robust," that is, if they are likely to work well in practice.Subjects

feedback control | feedback control | feedback control system | feedback control system | state-space | state-space | controllability | controllability | observability | observability | transfer functions | transfer functions | canonical forms | canonical forms | controllers | controllers | pole-placement | pole-placement | optimal control | optimal control | Kalman filter | Kalman filterLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.002 Circuits and Electronics (MIT) 6.002 Circuits and Electronics (MIT)

Description

6.002 introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. Design and lab exercises are also significant components of the course. 6.002 is worth 4 Engineering Design Points. 6.002 introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. Design and lab exercises are also significant components of the course. 6.002 is worth 4 Engineering Design Points.Subjects

circuit | circuit | electronic | electronic | abstraction | abstraction | lumped circuit | lumped circuit | digital | digital | amplifier | amplifier | differential equations | differential equations | time behavior | time behavior | energy storage | energy storage | semiconductor diode | semiconductor diode | field-effect | field-effect | field-effect transistor | field-effect transistor | resistor | resistor | source | source | inductor | inductor | capacitor | capacitor | diode | diode | series-parallel reduction | series-parallel reduction | voltage | voltage | current divider | current divider | node method | node method | linearity | linearity | superposition | superposition | Thevenin-Norton equivalent | Thevenin-Norton equivalent | power flow | power flow | Boolean algebra | Boolean algebra | binary signal | binary signal | MOSFET | MOSFET | noise margin | noise margin | singularity functions | singularity functions | sinusoidal-steady-state | sinusoidal-steady-state | impedance | impedance | frequency response curves | frequency response curves | operational amplifier | operational amplifier | Op-Amp | Op-Amp | negative feedback | negative feedback | positive feedback | positive feedbackLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataRES.6-010 Electronic Feedback Systems (MIT) RES.6-010 Electronic Feedback Systems (MIT)

Description

Includes audio/video content: AV lectures. Feedback control is an important technique that is used in many modern electronic and electromechanical systems. The successful inclusion of this technique improves performance, reliability, and cost effectiveness of many designs. In this series of lectures we introduce the analytical concepts that underlie classical feedback system design. The application of these concepts is illustrated by a variety of experiments and demonstration systems. The diversity of the demonstration systems reinforces the value of the analytic methods. Includes audio/video content: AV lectures. Feedback control is an important technique that is used in many modern electronic and electromechanical systems. The successful inclusion of this technique improves performance, reliability, and cost effectiveness of many designs. In this series of lectures we introduce the analytical concepts that underlie classical feedback system design. The application of these concepts is illustrated by a variety of experiments and demonstration systems. The diversity of the demonstration systems reinforces the value of the analytic methods.Subjects

electronic feedback systems | electronic feedback systems | operational amplifiers | operational amplifiers | electromagnetic fields | electromagnetic fields | stability | stability | root locus | root locus | feedback compensation | feedback compensation | nonlinearities | nonlinearities | system dynamics | system dynamicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This course focuses on the design of control systems. Topics covered include: frequency domain and state space techniques; control law design using Nyquist diagrams and Bode plots; state feedback, state estimation, and the design of dynamic control laws; and elementary analysis of nonlinearities and their impact on control design. There is extensive use of computer-aided control design tools. Applications to various aerospace systems, including navigation, guidance, and control of vehicles, are also discussed. This course focuses on the design of control systems. Topics covered include: frequency domain and state space techniques; control law design using Nyquist diagrams and Bode plots; state feedback, state estimation, and the design of dynamic control laws; and elementary analysis of nonlinearities and their impact on control design. There is extensive use of computer-aided control design tools. Applications to various aerospace systems, including navigation, guidance, and control of vehicles, are also discussed.Subjects

estimation of aerospace systems | estimation of aerospace systems | control of aerospace systems | control of aerospace systems | control systems | control systems | frequency domain | frequency domain | state space | state space | control law design | control law design | Nyquist diagram | Nyquist diagram | Bode plot | Bode plot | state feedback | state feedback | state estimation | state estimation | dynamic control | dynamic control | nonlinearities | nonlinearities | nonlinearity | nonlinearity | control design | control design | computer-aided control design | computer-aided control design | feedback control system | feedback control systemLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata21L.448J Darwin and Design (MIT) 21L.448J Darwin and Design (MIT)

Description

This subject offers a broad survey of texts (both literary and philosophical) drawn from the Western tradition and selected to trace the immediate intellectual antecedents and some of the implications of the ideas animating Darwin's revolutionary On the Origin of Species. Darwin's text, of course, is about the mechanism that drives the evolution of life on this planet, but the fundamental ideas of the text have implications that range well beyond the scope of natural history, and the assumptions behind Darwin's arguments challenge ideas that go much further back than the set of ideas that Darwin set himself explicitly to question - ideas of decisive importance when we think about ourselves, the nature of the material universe, the planet that we live upon, and our place in its scheme of This subject offers a broad survey of texts (both literary and philosophical) drawn from the Western tradition and selected to trace the immediate intellectual antecedents and some of the implications of the ideas animating Darwin's revolutionary On the Origin of Species. Darwin's text, of course, is about the mechanism that drives the evolution of life on this planet, but the fundamental ideas of the text have implications that range well beyond the scope of natural history, and the assumptions behind Darwin's arguments challenge ideas that go much further back than the set of ideas that Darwin set himself explicitly to question - ideas of decisive importance when we think about ourselves, the nature of the material universe, the planet that we live upon, and our place in its scheme ofSubjects

Origin of Species | Origin of Species | Darwin | Darwin | intelligent agency | intelligent agency | literature | literature | speculative thought | speculative thought | eighteenth century | eighteenth century | feedback mechanism | feedback mechanism | artificial intelligence | artificial intelligence | Hume | Hume | Voltaire | Voltaire | Malthus | Malthus | Butler | Butler | Hardy | Hardy | H.G. Wells | H.G. Wells | Freud | Freud | artificial | artificial | intelligence | intelligence | feedback | feedback | mechanism | mechanism | speculative | speculative | thought | thought | intelligent | intelligent | agency | agency | systems | systems | design | design | pre-Darwinian | pre-Darwinian | Darwinian | Darwinian | natural | natural | history | history | conscious | conscious | selection | selection | chance | chance | unconscious | unconscious | philosophy | philosophy | human | human | Adam Smith | Adam Smith | Thomas Malthus | Thomas Malthus | intellectual | intellectual | self-guiding | self-guiding | self-sustaining | self-sustaining | nature | nature | unintelligent | unintelligent | mechanical | mechanical | argument | argument | evolution | evolution | creation | creation | creationism | creationism | ethics | ethics | ethical | ethical | values | values | On the Origin of Species | On the Origin of Species | Charles Darwin | Charles Darwin | model | model | existence | existence | objects | objects | designer | designer | purpose | purpose | literary texts | literary texts | philosophical texts | philosophical texts | Western tradition | Western tradition | intellectual history | intellectual history | life | life | planet | planet | natural history | natural history | material universe | material universe | theory of natural selection | theory of natural selection | argument from design | argument from design | organisms | organisms | human design | human design | conscious agency | conscious agency | unconscious agency | unconscious agency | human intelligence | human intelligence | self-guiding systems | self-guiding systems | self-sustaining systems | self-sustaining systems | natural selection | natural selection | 21L.448 | 21L.448 | 21W.739 | 21W.739License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This course develops the fundamentals of feedback control using linear transfer function system models. Topics covered include analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and use of z-plane design. Students will complete an extended design case study. Students taking the graduate version (2.140) will attend the recitation sessions and complete additional assignments. This course develops the fundamentals of feedback control using linear transfer function system models. Topics covered include analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and use of z-plane design. Students will complete an extended design case study. Students taking the graduate version (2.140) will attend the recitation sessions and complete additional assignments.Subjects

feedback loops | feedback loops | control systems | control systems | compensation | compensation | Bode plots | Bode plots | Nyquist plots | Nyquist plots | state space | state space | frequency domain | frequency domain | time domain | time domain | transfer functions | transfer functions | Laplace transform | Laplace transform | root locus | root locus | op-amps | op-amps | gears | gears | motors | motors | actuators | actuators | nonlinear systems | nonlinear systems | stability theory | stability theory | dynamic feedback | dynamic feedback | mechanical engineering problem archive | mechanical engineering problem archiveLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataLecture 9: Strategy, Skill, and Chance, Part 2 Lecture 9: Strategy, Skill, and Chance, Part 2

Description

Description: This lecture reviews the concepts of information flow and uncertainty, analyzing well-known games in these terms. Examples include Scrabble, Go Fish, Mario Kart, Monopoly, chess, poker, War, and Settlers of Catan. Next, students consider feedback loops. Instructors/speakers: Philip Tan, Jason BegyKeywords: complexity, determinism, randomness, uncertainty, strategy, games of skill, games of chance, playtesting, information theory, risk, game state, board games, probability, cybernetics, positive feedback loop, negative feedback loopTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA) Description: This lecture reviews the concepts of information flow and uncertainty, analyzing well-known games in these terms. Examples include Scrabble, Go Fish, Mario Kart, Monopoly, chess, poker, War, and Settlers of Catan. Next, students consider feedback loops. Instructors/speakers: Philip Tan, Jason BegyKeywords: complexity, determinism, randomness, uncertainty, strategy, games of skill, games of chance, playtesting, information theory, risk, game state, board games, probability, cybernetics, positive feedback loop, negative feedback loopTranscript: PDFSubtitles: SRTAudio - download: Internet Archive (MP3)Audio - download: iTunes U (MP3)(CC BY-NC-SA)Subjects

complexity | complexity | determinism | determinism | randomness | randomness | uncertainty | uncertainty | strategy | strategy | games of skill | games of skill | games of chance | games of chance | playtesting | playtesting | information theory | information theory | risk | risk | game state | game state | board games | board games | probability | probability | cybernetics | cybernetics | positive feedback loop | positive feedback loop | negative feedback loop | negative feedback loopLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataDG2W35 Active Electronic Circuits

Description

This unit is designed to enable candidates to build on their knowledge of analogue electronic principles with regards to further understanding of electronic circuits. It will allow the candidate to gain an understanding of feedback and to develop this understanding with regards to a specified list of electronic amplifiers, filters and oscillator circuits. In addition, candidates will design a second-order filter using a reference table provided. The candidates will be required to perform practical tests on a circuit from the list. On completion of this unit the candidate should be able to: 1. analyse the effects of positive and negative feedback 2. analyse the circuits and properties of common operational amplifier circuits 3. outline the properties of filters 4. outline the operation of eSubjects

DG2W 35 | Feedback configurations | Series voltage feedback | Series current negative feedback | Shunt voltage negative feedback | Shunt current negative feedback | Frequency response | AC amplifiers | Distortion | Thermal noise | Signal to noise ratio | Integrator | Differentiator | Active filters | Sallenâ€“Key filter | SCQF Level 8License

Licensed to colleges in Scotland only Licensed to colleges in Scotland only Except where expressly indicated otherwise on the face of these materials (i) copyright in these materials is owned by the Scottish Qualification Authority (SQA), and (ii) none of these materials may be Used without the express, prior, written consent of the Colleges Open Learning Exchange Group (COLEG) and SQA, except if and to the extent that such Use is permitted under COLEG's conditions of Contribution and Use of Learning Materials through COLEGâ€™s Repository, for the purposes of which these materials are COLEG Materials, Except where expressly indicated otherwise on the face of these materials (i) copyright in these materials is owned by the Scottish Qualification Authority (SQA), and (ii) none of these materials may be Used without the express, prior, written consent of the Colleges Open Learning Exchange Group (COLEG) and SQA, except if and to the extent that such Use is permitted under COLEG's conditions of Contribution and Use of Learning Materials through COLEGâ€™s Repository, for the purposes of which these materials are COLEG Materials, http://content.resourceshare.ac.uk/xmlui/bitstream/handle/10949/17761/LicenceSQAMaterialsCOLEG.pdf?sequence=1 http://content.resourceshare.ac.uk/xmlui/bitstream/handle/10949/17761/LicenceSQAMaterialsCOLEG.pdf?sequence=1 SQA SQASite sourced from

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See all metadata2.18 Biomolecular Feedback Systems (MIT) 2.18 Biomolecular Feedback Systems (MIT)

Description

This course focuses on feedback control mechanisms that living organisms implement at the molecular level to execute their functions, with emphasis on techniques to design novel systems with prescribed behaviors. Students will learn how biological functions can be understood and designed using notions from feedback control. This course focuses on feedback control mechanisms that living organisms implement at the molecular level to execute their functions, with emphasis on techniques to design novel systems with prescribed behaviors. Students will learn how biological functions can be understood and designed using notions from feedback control.Subjects

biomolecular feedback systems | biomolecular feedback systems | systems biology | systems biology | modeling | modeling | feedback | feedback | cell | cell | system | system | control | control | dynamical | dynamical | input/output | input/output | synthetic biology | synthetic biology | techniques | techniques | transcription | transcription | translation | translation | transcriptional regulation | transcriptional regulation | post-transcriptional regulation | post-transcriptional regulation | cellular subsystems | cellular subsystems | dynamic behavior | dynamic behavior | analysis | analysis | equilibrium | equilibrium | robustness | robustness | oscillatory behavior | oscillatory behavior | bifurcations | bifurcations | model reduction | model reduction | stochastic | stochastic | biochemical | biochemical | simulation | simulation | linear | linear | circuit | circuit | design | design | biological circuit design | biological circuit design | negative autoregulation | negative autoregulation | toggle switch | toggle switch | repressilator | repressilator | activator-repressor clock | activator-repressor clock | IFFL | IFFL | incoherent feedforward loop | incoherent feedforward loop | bacterial chemotaxis | bacterial chemotaxis | interconnecting components | interconnecting components | modularity | modularity | retroactivity | retroactivity | gene circuit | gene circuitLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This course develops the fundamentals of feedback control using linear transfer function system models. It covers analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and the use of z-plane design. Assignments include extended design case studies and capstone group projects. Graduate students are expected to complete additional assignments. This course develops the fundamentals of feedback control using linear transfer function system models. It covers analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and the use of z-plane design. Assignments include extended design case studies and capstone group projects. Graduate students are expected to complete additional assignments.Subjects

feedback loops | feedback loops | compensation | compensation | Bode plots | Bode plots | Nyquist plots | Nyquist plots | state space | state space | frequency domain | frequency domain | time domain | time domain | transfer functions | transfer functions | Laplace transform | Laplace transform | root locus | root locus | op-amps | op-amps | gears | gears | motors | motors | actuators | actuators | nonlinear systems | nonlinear systems | stability theory | stability theory | control systems | control systems | dynamic feedback | dynamic feedback | mechanical engineering problem archive | mechanical engineering problem archiveLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataTechniques to Encourage Learning through Feedback - Mini Lecture

Description

A mini-lecture which examines Techniques to Encourage Learning Through Feedback and the Barriers to Effective FeedbackSubjects

feedback | effective feedback | barriers to feedback | communication | employability | ukoer | administrative studies | N000License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

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See all metadata16.30 Feedback Control Systems (MIT)

Description

This course will teach fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, you should be able to design controllers using state-space methods and evaluate whether these controllers are robust to some types of modeling errors and nonlinearities. You will learn to: Design controllers using state-space methods and analyze using classical tools. Understand impact of implementation issues (nonlinearity, delay). Indicate the robustness of your control design. Linearize a nonlinear system, and analyze stability.Subjects

control design | control analysis | state-space methods | linear systems | estimation filters | dynamic output feedback | full state feedback | state estimation | output feedback | nonlinear analysis | model uncertainty | robustnessLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.832 Underactuated Robotics (MIT)

Description

Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which involve a loss of instantaneous control authority. Controlling nonlinear systems without complete control authority requires methods that can reason about and exploit the natural dynamics of our machines. This course discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods. Topics include nonlinear dynamics of passive robots (walkers, swimmers, flyers), motion planning, partial feedback linearization, energy-shaping control, analytical optimal control, reinforcement learning/approximate optimal control, and the influenSubjects

underactuated robotics | actuated systems | nonlinear dynamics | simple pendulum | optimal control | double integrator | quadratic regulator | Hamilton-Jacobi-Bellman sufficiency | minimum time control | acrobot | cart-pole | partial feedback linearization | energy shaping | policy search | open-loop optimal control | trajectory stabilization | iterative linear quadratic regulator | differential dynamic programming | walking models | rimless wheel | compass gait | kneed compass gait | feedback control | running models | spring-loaded inverted pendulum | Raibert hoppers | motion planning | randomized motion planning | rapidly-exploring randomized trees | probabilistic road maps | feedback motion planning | planning with funnels | linear quadratic regulator | function approximation | state distribution dynamics | state estimation | stochastic optimal control | aircraft | swimming | flapping flight | randomized policy gradient | model-free value methods | temporarl difference learning | Q-learning | actor-critic methodsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataFeedback Electronics Feedback Electronics

Description

This course presents the basics of electronic circuits with feedback. This course presents the basics of electronic circuits with feedback.Subjects

feedback electronics | feedback electronics | ía Electrónica | ía Electrónica | 2009 | 2009 | ía Industrial | ía IndustrialLicense

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See all metadata6.003 Signals and Systems (MIT) 6.003 Signals and Systems (MIT)

Description

6.003 covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing. 6.003 covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.Subjects

signal and system analysis | signal and system analysis | representations of discrete-time and continuous-time signals | representations of discrete-time and continuous-time signals | representations of linear time-invariant systems | representations of linear time-invariant systems | Fourier representations | Fourier representations | Laplace and Z transforms | Laplace and Z transforms | sampling | sampling | difference and differential equations | difference and differential equations | feedback and control | feedback and control | communications | communications | signal processing | signal processingLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata5.95J Teaching College-Level Science (MIT) 5.95J Teaching College-Level Science (MIT)

Description

This seminar focuses on the knowledge and skills necessary for teaching science and engineering in higher education. Topics include: using current research in student learning to improve teaching; developing courses; lecturing; promoting students' ability to think critically and solve problems; communicating with a diverse student body; using educational technology; creating effective assignments and tests; and utilizing feedback to improve instruction. Students research and teach a topic of particular interest. This subject is appropriate for both novices and those with teaching experience. This seminar focuses on the knowledge and skills necessary for teaching science and engineering in higher education. Topics include: using current research in student learning to improve teaching; developing courses; lecturing; promoting students' ability to think critically and solve problems; communicating with a diverse student body; using educational technology; creating effective assignments and tests; and utilizing feedback to improve instruction. Students research and teach a topic of particular interest. This subject is appropriate for both novices and those with teaching experience.Subjects

teaching skills | teaching skills | learning objectives | learning objectives | lecturing | lecturing | active learning | active learning | feedback | feedback | interactive lessons | interactive lessons | pedagogy | pedagogy | student learning | student learning | educational technology | educational technology | STEM (science | STEM (science | technology | technology | engineering | engineering | and mathematics) | and mathematics) | teaching philosophy statement | teaching philosophy statement | 5.95 | 5.95 | 7.59 | 7.59 | 8.395 | 8.395 | 18.094 | 18.094License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata21L.448J Darwin and Design (MIT) 21L.448J Darwin and Design (MIT)

Description

In the Origin of Species (1859), Charles Darwin gave us a model for understanding how natural objects and systems can evidence design without positing a designer: how purpose and mechanism can exist without intelligent agency. Texts in this course deal with pre- and post-Darwinian treatment of this topic within literature and speculative thought since the eighteenth century. We will give some attention to the modern study of feedback mechanisms in artificial intelligence. Our reading will be in Hume, Voltaire, Malthus, Darwin, Butler, H. G. Wells, and Turing. In the Origin of Species (1859), Charles Darwin gave us a model for understanding how natural objects and systems can evidence design without positing a designer: how purpose and mechanism can exist without intelligent agency. Texts in this course deal with pre- and post-Darwinian treatment of this topic within literature and speculative thought since the eighteenth century. We will give some attention to the modern study of feedback mechanisms in artificial intelligence. Our reading will be in Hume, Voltaire, Malthus, Darwin, Butler, H. G. Wells, and Turing.Subjects

Origin of Species | Origin of Species | Darwin | Darwin | intelligent agency | intelligent agency | literature | literature | speculative thought | speculative thought | eighteenth century | eighteenth century | feedback mechanism | feedback mechanism | artificial intelligence | artificial intelligence | Hume | Hume | Voltaire | Voltaire | Malthus | Malthus | Butler | Butler | Hardy | Hardy | H.G. Wells | H.G. Wells | Freud | Freud | Evolution | Evolution | Modern Western philosophy | Modern Western philosophy | Philosophy of science | Philosophy of science | Religion | Religion | Science | Science | Life Sciences | Life Sciences | Social Aspects | Social Aspects | History | History | Intelligent design | individual species | Intelligent design | individual species | complexity | complexity | development | development | God theory of evolution | God theory of evolution | science | science | theological explanation | theological explanation | universe | universe | creatures | creatures | faith | faith | and theology | and theology | purpose of evolution | purpose of evolution | Design | Design | models | models | adaptation | adaptationLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata2.019 Design of Ocean Systems (MIT) 2.019 Design of Ocean Systems (MIT)

Description

This course is the completion of the cycle of designing, implementing and testing an ocean system, including hardware and software implementation, that begins with 2.017J. Design lectures are given in hydrodynamics, power and thermal aspects of ocean vehicles, environment, materials and construction for ocean use, electronics, sensors, and actuators. Student teams work within schedule and budget, setting goals, reviewing progress, and making regular and final presentations. Instruction and practice occur in oral and written communication. This course is the completion of the cycle of designing, implementing and testing an ocean system, including hardware and software implementation, that begins with 2.017J. Design lectures are given in hydrodynamics, power and thermal aspects of ocean vehicles, environment, materials and construction for ocean use, electronics, sensors, and actuators. Student teams work within schedule and budget, setting goals, reviewing progress, and making regular and final presentations. Instruction and practice occur in oral and written communication.Subjects

hydrodynamics | hydrodynamics | power and thermal aspects of ocean vehicles | power and thermal aspects of ocean vehicles | environment | environment | electronics | electronics | sensors | sensors | actuators | actuators | sea-keeping | sea-keeping | hull strength | hull strength | physics of acoustics | physics of acoustics | resistance | resistance | propulsion | propulsion | control surfaces | control surfaces | dynamics | dynamics | feedback control | feedback control | graphical information systems | graphical information systems | GIS | GISLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata16.31 Feedback Control Systems (MIT) 16.31 Feedback Control Systems (MIT)

Description

This course covers the fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, the student should be able to design controllers using state-space methods and evaluate whether these controllers are robust. This course covers the fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, the student should be able to design controllers using state-space methods and evaluate whether these controllers are robust.Subjects

linear system response | linear system response | aircraft control | aircraft control | frequency response methods | frequency response methods | Nyquist stability theorem | Nyquist stability theorem | bode plots | bode plots | state-space systems | state-space systems | full-state feedback control | full-state feedback control | open-loop estimators | open-loop estimators | closed-loop estimators | closed-loop estimators | robustness analysis | robustness analysis | small gain theorem | small gain theoremLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.003 Signals and Systems (MIT) 6.003 Signals and Systems (MIT)

Description

This course covers fundamentals of signal and system analysis, with applications drawn from filtering, audio and image processing, communications, and automatic control. Topics include convolution, Fourier series and transforms, sampling and discrete-time processing of continuous-time signals, modulation, Laplace and Z-transforms, and feedback systems. This course covers fundamentals of signal and system analysis, with applications drawn from filtering, audio and image processing, communications, and automatic control. Topics include convolution, Fourier series and transforms, sampling and discrete-time processing of continuous-time signals, modulation, Laplace and Z-transforms, and feedback systems.Subjects

signal and system analysis | signal and system analysis | filtering | filtering | audio | audio | audio processing | audio processing | image processing | image processing | communications | communications | automatic control | automatic control | convolution | convolution | Fourier series | Fourier series | fourier transforms | fourier transforms | sampling | sampling | discrete-time processing | discrete-time processing | modulation | modulation | Laplace transforms | Laplace transforms | Z-transforms | Z-transforms | feedback systems | feedback systemsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata21L.448 Darwin and Design (MIT) 21L.448 Darwin and Design (MIT)

Description

In the Origin of Species, Charles Darwin gave us a model for understanding how natural objects and systems can evidence design without positing a designer: how purpose and mechanism can exist without intelligent agency. Texts in this course deal with pre- and post-Darwinian treatment of this topic within literature and speculative thought since the eighteenth century. We will give some attention to the modern study of 'feedback mechanisms' in artificial intelligence. Our reading will be in Hume, Voltaire, Malthus, Darwin, Butler, Hardy, H. G. Wells, and Turing. There will be about 100 pages of weekly reading--sometimes fewer, sometimes more. Note: The title and content of this course, taught steadily at MIT since 1987, predate Michael Ruse's recent 2003 volume by the same titl In the Origin of Species, Charles Darwin gave us a model for understanding how natural objects and systems can evidence design without positing a designer: how purpose and mechanism can exist without intelligent agency. Texts in this course deal with pre- and post-Darwinian treatment of this topic within literature and speculative thought since the eighteenth century. We will give some attention to the modern study of 'feedback mechanisms' in artificial intelligence. Our reading will be in Hume, Voltaire, Malthus, Darwin, Butler, Hardy, H. G. Wells, and Turing. There will be about 100 pages of weekly reading--sometimes fewer, sometimes more. Note: The title and content of this course, taught steadily at MIT since 1987, predate Michael Ruse's recent 2003 volume by the same titlSubjects

Origin of Species | Origin of Species | Darwin | Darwin | intelligent agency | intelligent agency | literature | literature | speculative thought | speculative thought | eighteenth century | eighteenth century | feedback mechanism | feedback mechanism | artificial intelligence | artificial intelligence | Hume | Hume | Voltaire | Voltaire | Malthus | Malthus | Butler | Butler | Hardy | Hardy | H.G. Wells | H.G. Wells | Freud | Freud | 21W.739 | 21W.739License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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