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16.31 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 filter

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2.019 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 | GIS

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16.31 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 theorem

License

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2.830J Control of Manufacturing Processes (SMA 6303) (MIT) 2.830J Control of Manufacturing Processes (SMA 6303) (MIT)

Description

The objective of this subject is to understand the nature of manufacturing process variation and the methods for its control. First, a general process model for control is developed to understand the limitations a specific process places on the type of control used. A general model for process variation is presented and three methods are developed to minimize variations: Statistical Process Control, Process Optimization and in-process Feedback Control. These are considered in a hierarchy of cost-performance tradeoffs, where performance is based on changes in process capability.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6306 (Manufacturing Physics III: Process Optimisation and Control). The objective of this subject is to understand the nature of manufacturing process variation and the methods for its control. First, a general process model for control is developed to understand the limitations a specific process places on the type of control used. A general model for process variation is presented and three methods are developed to minimize variations: Statistical Process Control, Process Optimization and in-process Feedback Control. These are considered in a hierarchy of cost-performance tradeoffs, where performance is based on changes in process capability.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6306 (Manufacturing Physics III: Process Optimisation and Control).

Subjects

Process control | Process control | manufacturing process | manufacturing process | discrete system feedback control theory | discrete system feedback control theory | empirical and adaptive modeling | empirical and adaptive modeling | off-line optimization | off-line optimization | statistical process control | statistical process control | real-time control. | real-time control. | real-time control | real-time control | 2.830 | 2.830

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6.642 Continuum Electromechanics (MIT) 6.642 Continuum Electromechanics (MIT)

Description

This course focuses on laws, approximations, and relations of continuum electromechanics. Topics include mechanical and electromechanical transfer relations, statics and dynamics of electromechanical systems having a static equilibrium, electromechanical flows, and field coupling with thermal and molecular diffusion. See the syllabus section for a more detailed list of topics. This course focuses on laws, approximations, and relations of continuum electromechanics. Topics include mechanical and electromechanical transfer relations, statics and dynamics of electromechanical systems having a static equilibrium, electromechanical flows, and field coupling with thermal and molecular diffusion. See the syllabus section for a more detailed list of topics.

Subjects

continuum mechanics | continuum mechanics | electromechanics | electromechanics | mechanical and electromechanical transfer relations | mechanical and electromechanical transfer relations | statics | statics | dynamics | dynamics | electromechanical systems | electromechanical systems | static equililbrium | static equililbrium | electromechanical flows | electromechanical flows | field coupling | field coupling | thermal and molecular diffusion | thermal and molecular diffusion | electrokinetics | electrokinetics | streaming interactions | streaming interactions | materials processing | materials processing | magnetohydrodynamic and electrohydrodynamic pumps and generators | magnetohydrodynamic and electrohydrodynamic pumps and generators | ferrohydrodynamics | ferrohydrodynamics | physiochemical systems | physiochemical systems | heat transfer | heat transfer | continuum feedback control | continuum feedback control | electron beam devices | electron beam devices | plasma dynamics | plasma dynamics

License

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HST.723 Neural Coding and Perception of Sound (MIT) HST.723 Neural Coding and Perception of Sound (MIT)

Description

Neural structures and mechanisms mediating the detection, localization and recognition of sounds. We will discuss how acoustic signals are coded by auditory neurons, the impact of these codes on behavioral performance, and the circuitry and cellular mechanisms underlying signal transformations. Topics include temporal coding, neural maps and feature detectors, learning and plasticity, and feedback control. General principles are conveyed by theme discussions of auditory masking, sound localization, musical pitch, speech coding, and cochlear implants. Neural structures and mechanisms mediating the detection, localization and recognition of sounds. We will discuss how acoustic signals are coded by auditory neurons, the impact of these codes on behavioral performance, and the circuitry and cellular mechanisms underlying signal transformations. Topics include temporal coding, neural maps and feature detectors, learning and plasticity, and feedback control. General principles are conveyed by theme discussions of auditory masking, sound localization, musical pitch, speech coding, and cochlear implants.

Subjects

hearing | hearing | neural structures | neural structures | auditory masking | auditory masking | acoustics | acoustics | signal transformations | signal transformations | temporal coding | temporal coding | neural maps | neural maps | feature detectors | feature detectors | learning | learning | plasticity | plasticity | feedback control | feedback control | sound localization | sound localization | musical pitch | musical pitch | speech coding | speech coding | cochlear implants | cochlear implants

License

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6.832 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/a

Subjects

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 methods

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6.642 Continuum Electromechanics (MIT) 6.642 Continuum Electromechanics (MIT)

Description

Includes audio/video content: AV faculty introductions. This course focuses on laws, approximations and relations of continuum electromechanics. Topics include mechanical and electromechanical transfer relations, statics and dynamics of electromechanical systems having a static equilibrium, electromechanical flows, and field coupling with thermal and molecular diffusion. Also covered are electrokinetics, streaming interactions, application to materials processing, magnetohydrodynamic and electrohydrodynamic pumps and generators, ferrohydrodynamics, physiochemical systems, heat transfer, continuum feedback control, electron beam devices, and plasma dynamics. Acknowledgements The instructor would like to thank Xuancheng Shao and Anyang Hou for transcribing into LaTeX the problem set solution Includes audio/video content: AV faculty introductions. This course focuses on laws, approximations and relations of continuum electromechanics. Topics include mechanical and electromechanical transfer relations, statics and dynamics of electromechanical systems having a static equilibrium, electromechanical flows, and field coupling with thermal and molecular diffusion. Also covered are electrokinetics, streaming interactions, application to materials processing, magnetohydrodynamic and electrohydrodynamic pumps and generators, ferrohydrodynamics, physiochemical systems, heat transfer, continuum feedback control, electron beam devices, and plasma dynamics. Acknowledgements The instructor would like to thank Xuancheng Shao and Anyang Hou for transcribing into LaTeX the problem set solution

Subjects

continuum mechanics | continuum mechanics | electromechanics | electromechanics | mechanical and electromechanical transfer relations | mechanical and electromechanical transfer relations | statics | statics | dynamics | dynamics | electromechanical systems | electromechanical systems | static equililbrium | static equililbrium | electromechanical flows | electromechanical flows | field coupling | field coupling | thermal and molecular diffusion | thermal and molecular diffusion | electrokinetics | electrokinetics | streaming interactions | streaming interactions | materials processing | materials processing | magnetohydrodynamic and electrohydrodynamic pumps and generators | magnetohydrodynamic and electrohydrodynamic pumps and generators | ferrohydrodynamics | ferrohydrodynamics | physiochemical systems | physiochemical systems | heat transfer | heat transfer | continuum feedback control | continuum feedback control | electron beam devices | electron beam devices | plasma dynamics | plasma dynamics

License

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2.830J Control of Manufacturing Processes (SMA 6303) (MIT) 2.830J Control of Manufacturing Processes (SMA 6303) (MIT)

Description

Includes audio/video content: AV special element video, AV lectures. This course explores statistical modeling and control in manufacturing processes. Topics include the use of experimental design and response surface modeling to understand manufacturing process physics, as well as defect and parametric yield modeling and optimization. Various forms of process control, including statistical process control, run by run and adaptive control, and real-time feedback control, are covered. Application contexts include semiconductor manufacturing, conventional metal and polymer processing, and emerging micro-nano manufacturing processes. Includes audio/video content: AV special element video, AV lectures. This course explores statistical modeling and control in manufacturing processes. Topics include the use of experimental design and response surface modeling to understand manufacturing process physics, as well as defect and parametric yield modeling and optimization. Various forms of process control, including statistical process control, run by run and adaptive control, and real-time feedback control, are covered. Application contexts include semiconductor manufacturing, conventional metal and polymer processing, and emerging micro-nano manufacturing processes.

Subjects

2.830 | 2.830 | 6.780 | 6.780 | ESD.63 | ESD.63 | Process control | Process control | manufacturing process | manufacturing process | discrete system feedback control theory | discrete system feedback control theory | empirical and adaptive modeling | empirical and adaptive modeling | off-line optimization | off-line optimization | statistical process control | statistical process control | real-time control. | real-time control. | real-time control | real-time control | one-factor-at-a-time | one-factor-at-a-time | robustness | robustness | Shewhart Hypothesis | Shewhart Hypothesis | semiconductor manufacturing | semiconductor manufacturing

License

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1.571 Structural Analysis and Control (MIT) 1.571 Structural Analysis and Control (MIT)

Description

This course uses computer-based methods for the analysis of large-scale structural systems. Topics covered include: modeling strategies for complex structures; application to tall buildings, cable-stayed bridges, and tension structures; introduction to the theory of active structural control; design of classical feedback control systems for civil structures; and simulation studies using customized computer software. This course uses computer-based methods for the analysis of large-scale structural systems. Topics covered include: modeling strategies for complex structures; application to tall buildings, cable-stayed bridges, and tension structures; introduction to the theory of active structural control; design of classical feedback control systems for civil structures; and simulation studies using customized computer software.

Subjects

structural analysis | structural analysis | structures | structures | large-scale structural systems | large-scale structural systems | modeling | modeling | tall buildings | tall buildings | cable-stayed bridges | cable-stayed bridges | tension structures | tension structures | active structural control | active structural control | feedback control systems | feedback control systems | civil structures | civil structures | simulations | simulations

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2.017J Design of Electromechanical Robotic Systems (MIT) 2.017J Design of Electromechanical Robotic Systems (MIT)

Description

This course covers the design, construction, and testing of field robotic systems, through team projects with each student responsible for a specific subsystem. Projects focus on electronics, instrumentation, and machine elements. Design for operation in uncertain conditions is a focus point, with ocean waves and marine structures as a central theme. Topics include basic statistics, linear systems, Fourier transforms, random processes, spectra, ethics in engineering practice, and extreme events with applications in design. This course covers the design, construction, and testing of field robotic systems, through team projects with each student responsible for a specific subsystem. Projects focus on electronics, instrumentation, and machine elements. Design for operation in uncertain conditions is a focus point, with ocean waves and marine structures as a central theme. Topics include basic statistics, linear systems, Fourier transforms, random processes, spectra, ethics in engineering practice, and extreme events with applications in design.

Subjects

optimization | optimization | random environment | random environment | linear time invariant systems | linear time invariant systems | navigation systems | navigation systems | engineering ethics | engineering ethics | spectra | spectra | probability of failure | probability of failure | frequency response | frequency response | Fourier transform | Fourier transform | convolution | convolution | extreme events | extreme events | feedback control | feedback control | statistics | statistics | machine elements | machine elements

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2.004 Dynamics and Control II (MIT) 2.004 Dynamics and Control II (MIT)

Description

Upon successful completion of this course, students will be able to: Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domains Make quantitative estimates of model parameters from experimental measurements Obtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methods Obtain the frequency-domain response of linear systems to sinusoidal inputs Compensate the transient response of dynamic systems using feedback techniques Design, implement and test an active control system to achieve a desired performance measure Mastery of these topics will be assessed via homework, quizzes/exams, and lab assig Upon successful completion of this course, students will be able to: Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domains Make quantitative estimates of model parameters from experimental measurements Obtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methods Obtain the frequency-domain response of linear systems to sinusoidal inputs Compensate the transient response of dynamic systems using feedback techniques Design, implement and test an active control system to achieve a desired performance measure Mastery of these topics will be assessed via homework, quizzes/exams, and lab assig

Subjects

Laplace transform | Laplace transform | transform function | transform function | electrical and mechanical systems | electrical and mechanical systems | pole-zero diagram | pole-zero diagram | linearization | linearization | block diagrams | block diagrams | feedback control systems | feedback control systems | stability | stability | root-locus plot | root-locus plot | compensation | compensation | Bode plot | Bode plot | state space representation | state space representation | minimum time | minimum time

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2.004 Systems, Modeling, and Control II (MIT) 2.004 Systems, Modeling, and Control II (MIT)

Description

Upon successful completion of this course, students will be able to:Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domainsMake quantitative estimates of model parameters from experimental measurementsObtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methodsObtain the frequency-domain response of linear systems to sinusoidal inputsCompensate the transient response of dynamic systems using feedback techniquesDesign, implement and test an active control system to achieve a desired performance measureMastery of these topics will be assessed via homework, quizzes/exams, and lab assignments. Upon successful completion of this course, students will be able to:Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domainsMake quantitative estimates of model parameters from experimental measurementsObtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methodsObtain the frequency-domain response of linear systems to sinusoidal inputsCompensate the transient response of dynamic systems using feedback techniquesDesign, implement and test an active control system to achieve a desired performance measureMastery of these topics will be assessed via homework, quizzes/exams, and lab assignments.

Subjects

Laplace transform | Laplace transform | transform function | transform function | electrical and mechanical systems | electrical and mechanical systems | pole-zero diagram | pole-zero diagram | linearization | linearization | block diagrams | block diagrams | feedback control systems | feedback control systems | stability | stability | root-locus plot | root-locus plot | compensation | compensation | Bode plot | Bode plot | state space representation | state space representation | minimum time | minimum time

License

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6.245 Multivariable Control Systems (MIT) 6.245 Multivariable Control Systems (MIT)

Description

This course uses computer-aided design methodologies for synthesis of multivariable feedback control systems. Topics covered include: performance and robustness trade-offs; model-based compensators; Q-parameterization; ill-posed optimization problems; dynamic augmentation; linear-quadratic optimization of controllers; H-infinity controller design; Mu-synthesis; model and compensator simplification; and nonlinear effects. The assignments for the course comprise of computer-aided (MATLAB®) design problems. This course uses computer-aided design methodologies for synthesis of multivariable feedback control systems. Topics covered include: performance and robustness trade-offs; model-based compensators; Q-parameterization; ill-posed optimization problems; dynamic augmentation; linear-quadratic optimization of controllers; H-infinity controller design; Mu-synthesis; model and compensator simplification; and nonlinear effects. The assignments for the course comprise of computer-aided (MATLAB®) design problems.

Subjects

multivariable control systems | multivariable control systems | computer-aided design | computer-aided design | MATLAB | MATLAB | multivariable feedback control systems | multivariable feedback control systems | model-based compensators | model-based compensators | Q-parameterization | Q-parameterization | optimization | optimization | dynamic augmentation | dynamic augmentation | linear-quadratic optimization | linear-quadratic optimization | H-infinity controller design | H-infinity controller design | Mu-synthesis | Mu-synthesis | nonlinear systems | nonlinear systems | engineering design | engineering design

License

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16.323 Principles of Optimal Control (MIT) 16.323 Principles of Optimal Control (MIT)

Description

This course studies basic optimization and the principles of optimal control. It considers deterministic and stochastic problems for both discrete and continuous systems. The course covers solution methods including numerical search algorithms, model predictive control, dynamic programming, variational calculus, and approaches based on Pontryagin's maximum principle, and it includes many examples and applications of the theory. This course studies basic optimization and the principles of optimal control. It considers deterministic and stochastic problems for both discrete and continuous systems. The course covers solution methods including numerical search algorithms, model predictive control, dynamic programming, variational calculus, and approaches based on Pontryagin's maximum principle, and it includes many examples and applications of the theory.

Subjects

nonlinear optimization | nonlinear optimization | dynamic programming | dynamic programming | HJB Equation | HJB Equation | calculus of variations | calculus of variations | constrained optimal control | constrained optimal control | singular arcs | singular arcs | stochastic optimal control | stochastic optimal control | LQG robustness | LQG robustness | feedback control systems | feedback control systems | model predictive control | model predictive control | line search methods | line search methods | Lagrange multipliers | Lagrange multipliers | discrete LQR | discrete LQR

License

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16.30 Estimation and Control of Aerospace Systems (MIT) 16.30 Estimation and Control of Aerospace Systems (MIT)

Description

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 system

License

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HST.720 Physiology of the Ear (MIT) HST.720 Physiology of the Ear (MIT)

Description

Topics for this course are based primarily on reading and discussions of original research literature that cover the analysis as well as the underlying physical and physiological mechanisms of acoustic signals in the auditory periphery. Topics include the acoustics, mechanics, and hydrodynamics of sound transmission; the biophysical basis for cochlear amplification; the physiology of hair-cell transduction and synaptic transmission; efferent feedback control; the analysis and coding of simple and complex sounds by the inner ear; and the physiological bases for hearing disorders. Topics for this course are based primarily on reading and discussions of original research literature that cover the analysis as well as the underlying physical and physiological mechanisms of acoustic signals in the auditory periphery. Topics include the acoustics, mechanics, and hydrodynamics of sound transmission; the biophysical basis for cochlear amplification; the physiology of hair-cell transduction and synaptic transmission; efferent feedback control; the analysis and coding of simple and complex sounds by the inner ear; and the physiological bases for hearing disorders.

Subjects

cochlear physiology | cochlear physiology | cochlea | cochlea | ear | ear | ear canal | ear canal | inner ear | inner ear | middle ear | middle ear | outer ear | outer ear | auditory pathway | auditory pathway | auditory nerve | auditory nerve | auditory brainstem | auditory brainstem | acoustic coupling | acoustic coupling | auditory periphery | auditory periphery | acoustic signals | acoustic signals | sound transmission | sound transmission | cochlear amplification | cochlear amplification | synaptic transmission | synaptic transmission | hair cell transduction | hair cell transduction | efferent feedback control | efferent feedback control | hearing disorders | hearing disorders | hearing | hearing | cochlear mechanics | cochlear mechanics | basilar membrane | basilar membrane | auditory nerve fiber response | auditory nerve fiber response | otoacoustic emissions | otoacoustic emissions | outer hair cell | outer hair cell

License

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.htm

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16.06 Principles of Automatic Control (MIT) 16.06 Principles of Automatic Control (MIT)

Description

This course introduces the design of feedback control systems as applied to a variety of air and spacecraft systems. Topics include the properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, the Root locus method, Nyquist criterion, frequency-domain design, and state space methods. This course introduces the design of feedback control systems as applied to a variety of air and spacecraft systems. Topics include the properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, the Root locus method, Nyquist criterion, frequency-domain design, and state space methods.

Subjects

classical control systems | classical control systems | feedback control systems | feedback control systems | bode plots | bode plots | time-domain and frequency-domain performance measures | time-domain and frequency-domain performance measures | stability | stability | root locus method | root locus method | nyquist criterion | nyquist criterion | frequency-domain design | frequency-domain design | state space methods | state space methods

License

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16.06 Principles of Automatic Control (MIT) 16.06 Principles of Automatic Control (MIT)

Description

The course deals with introduction to design of feedback control systems, properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability. It also covers root locus method, nyquist criterion, frequency-domain design, and state space methods. The course deals with introduction to design of feedback control systems, properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability. It also covers root locus method, nyquist criterion, frequency-domain design, and state space methods.

Subjects

feedback control systems | feedback control systems | time-domain and frequency-domain performance measures | time-domain and frequency-domain performance measures | stability | stability | root locus method | root locus method | nyquist criterion | nyquist criterion | frequency-domain design | frequency-domain design | state space methods | state space methods | time-domain performance measures | time-domain performance measures | frequency-domain performance measures | frequency-domain performance measures | aircraft systems | aircraft systems | spacecraft systems | spacecraft systems | control system analysis | control system analysis | time-domain system design | time-domain system design

License

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.htm

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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.

Subjects

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

License

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16.06 Principles of Automatic Control (MIT)

Description

The course deals with introduction to design of feedback control systems, properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability. It also covers root locus method, nyquist criterion, frequency-domain design, and state space methods.

Subjects

feedback control systems | time-domain and frequency-domain performance measures | stability | root locus method | nyquist criterion | frequency-domain design | state space methods | time-domain performance measures | frequency-domain performance measures | aircraft systems | spacecraft systems | control system analysis | time-domain system design

License

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.htm

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2.830J Control of Manufacturing Processes (SMA 6303) (MIT)

Description

This course explores statistical modeling and control in manufacturing processes. Topics include the use of experimental design and response surface modeling to understand manufacturing process physics, as well as defect and parametric yield modeling and optimization. Various forms of process control, including statistical process control, run by run and adaptive control, and real-time feedback control, are covered. Application contexts include semiconductor manufacturing, conventional metal and polymer processing, and emerging micro-nano manufacturing processes.

Subjects

2.830 | 6.780 | ESD.63 | Process control | manufacturing process | discrete system feedback control theory | empirical and adaptive modeling | off-line optimization | statistical process control | real-time control. | real-time control | one-factor-at-a-time | robustness | Shewhart Hypothesis | semiconductor manufacturing

License

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6.245 Multivariable Control Systems (MIT)

Description

This course uses computer-aided design methodologies for synthesis of multivariable feedback control systems. Topics covered include: performance and robustness trade-offs; model-based compensators; Q-parameterization; ill-posed optimization problems; dynamic augmentation; linear-quadratic optimization of controllers; H-infinity controller design; Mu-synthesis; model and compensator simplification; and nonlinear effects. The assignments for the course comprise of computer-aided (MATLAB®) design problems.

Subjects

multivariable control systems | computer-aided design | MATLAB | multivariable feedback control systems | model-based compensators | Q-parameterization | optimization | dynamic augmentation | linear-quadratic optimization | H-infinity controller design | Mu-synthesis | nonlinear systems | engineering design

License

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.htm

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1.571 Structural Analysis and Control (MIT)

Description

This course uses computer-based methods for the analysis of large-scale structural systems. Topics covered include: modeling strategies for complex structures; application to tall buildings, cable-stayed bridges, and tension structures; introduction to the theory of active structural control; design of classical feedback control systems for civil structures; and simulation studies using customized computer software.

Subjects

structural analysis | structures | large-scale structural systems | modeling | tall buildings | cable-stayed bridges | tension structures | active structural control | feedback control systems | civil structures | simulations

License

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.htm

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16.06 Principles of Automatic Control (MIT)

Description

The course deals with introduction to design of feedback control systems, properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability. It also covers root locus method, nyquist criterion, frequency-domain design, and state space methods.

Subjects

feedback control systems | time-domain and frequency-domain performance measures | stability | root locus method | nyquist criterion | frequency-domain design | state space methods | time-domain performance measures | frequency-domain performance measures | aircraft systems | spacecraft systems | control system analysis | time-domain system design

License

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.htm

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