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6.301 Solid-State Circuits (MIT) 6.301 Solid-State Circuits (MIT)

Description

This course covers analog circuit analysis and design, focusing on the tools and methods necessary for the creative design of useful circuits using active devices. The class stresses insight and intuition, applied to the design of transistor circuits and the estimation of their performance. The course concentrates on circuits using the bipolar junction transistor, but the techniques that are studied can be equally applied to circuits using JFETs, MOSFETs, MESFETs, future exotic devices, or even vacuum tubes. This course covers analog circuit analysis and design, focusing on the tools and methods necessary for the creative design of useful circuits using active devices. The class stresses insight and intuition, applied to the design of transistor circuits and the estimation of their performance. The course concentrates on circuits using the bipolar junction transistor, but the techniques that are studied can be equally applied to circuits using JFETs, MOSFETs, MESFETs, future exotic devices, or even vacuum tubes.Subjects

solid state circuits | solid state circuits | analog | analog | circuit | circuit | transistor | transistor | bipolar junction transistor | bipolar junction transistor | JFET | JFET | MOSFET | MOSFET | MESFET | MESFET | vacuum tubes | vacuum tubes | single-transistor common-emitter amplifier | single-transistor common-emitter amplifier | op amps | op amps | multipliers | multipliers | references | references | high speed logic | high speed logic | high-frequency analysis | high-frequency analysis | open-circuit time constants | open-circuit time constants | transimpedance amps | transimpedance amps | translinear circuits | translinear circuits | bandgap references | bandgap references | charge control model | charge control modelLicense

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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Includes audio/video content: AV lectures, AV faculty introductions. This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications. Note: This course was previously called "Mathematical Methods for Engineers I." Includes audio/video content: AV lectures, AV faculty introductions. This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications. Note: This course was previously called "Mathematical Methods for Engineers I."Subjects

linear algebra | linear algebra | networks | networks | Lagrange multipliers | Lagrange multipliers | differential equations of equilibrium | differential equations of equilibrium | Laplace's equation | Laplace's equation | potential flow | potential flow | boundary-value problems | boundary-value problems | Fourier series | Fourier series | discrete Fourier transform | discrete Fourier transform | convolution | convolutionLicense

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 metadata18.085 Mathematical Methods for Engineers I (MIT) 18.085 Mathematical Methods for Engineers I (MIT)

Description

This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications. This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.Subjects

linear algebra | linear algebra | networks | networks | Lagrange multipliers | Lagrange multipliers | differential equations of equilibrium | differential equations of equilibrium | Laplace's equation | Laplace's equation | potential flow | potential flow | boundary-value problems | boundary-value problems | Fourier series | Fourier series | discrete Fourier transform | discrete Fourier transform | convolution | convolutionLicense

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 metadata18.085 Mathematical Methods for Engineers I (MIT) 18.085 Mathematical Methods for Engineers I (MIT)

Description

Review of linear algebra, applications to networks, structures, and estimation, Lagrange multipliers, differential equations of equilibrium, Laplace's equation and potential flow, boundary-value problems, minimum principles and calculus of variations, Fourier series, discrete Fourier transform, convolution, applications.Technical RequirementsRealOne Player software is required to run the .rm files found on this course site. MATLAB® is a trademark of The MathWorks, Inc. Review of linear algebra, applications to networks, structures, and estimation, Lagrange multipliers, differential equations of equilibrium, Laplace's equation and potential flow, boundary-value problems, minimum principles and calculus of variations, Fourier series, discrete Fourier transform, convolution, applications.Technical RequirementsRealOne Player software is required to run the .rm files found on this course site. MATLAB® is a trademark of The MathWorks, Inc.Subjects

linear algebra | linear algebra | networks | networks | Lagrange multipliers | Lagrange multipliers | differential equations of equilibrium | differential equations of equilibrium | Laplace's equation | Laplace's equation | potential flow | potential flow | boundary-value problems | boundary-value problems | Fourier series | Fourier series | discrete Fourier transform | discrete Fourier transform | convolution | convolutionLicense

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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One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management. One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management.Subjects

modeling | modeling | optimization | optimization | simulation | simulation | manufacturing systems | manufacturing systems | decision making | decision making | decision support | decision support | probabilistic simulation | probabilistic simulation | designing manufacturing systems | designing manufacturing systems | operations management | operations management | linear programming | linear programming | sensitivity analysis | sensitivity analysis | network flow problems | network flow problems | non-linear programming | non-linear programming | Lagrange multipliers | Lagrange multipliers | integer programming | integer programming | discrete-event simulation | discrete-event simulation | heuristics | heuristics | algorithms | algorithms | 15.066 | 15.066 | 2.851 | 2.851 | 3.83 | 3.83License

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 provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.Note: This course was previously called "Mathematical Methods for Engineers I". This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.Note: This course was previously called "Mathematical Methods for Engineers I".Subjects

linear algebra | linear algebra | networks | networks | Lagrange multipliers | Lagrange multipliers | differential equations of equilibrium | differential equations of equilibrium | Laplace's equation | Laplace's equation | potential flow | potential flow | boundary-value problems | boundary-value problems | Fourier series | Fourier series | discrete Fourier transform | discrete Fourier transform | convolution | convolutionLicense

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 metadata6.331 Advanced Circuit Techniques (MIT) 6.331 Advanced Circuit Techniques (MIT)

Description

Following a brief classroom discussion of relevant principles, each student in this course completes the paper design of several advanced circuits such as multiplexers, sample-and-holds, gain-controlled amplifiers, analog multipliers, digital-to-analog or analog-to-digital converters, and power amplifiers. One of each student's designs is presented to the class, and one may be built and evaluated. Associated laboratory assignments emphasize the use of modern analog building blocks. This course is worth 12 Engineering Design Points. Following a brief classroom discussion of relevant principles, each student in this course completes the paper design of several advanced circuits such as multiplexers, sample-and-holds, gain-controlled amplifiers, analog multipliers, digital-to-analog or analog-to-digital converters, and power amplifiers. One of each student's designs is presented to the class, and one may be built and evaluated. Associated laboratory assignments emphasize the use of modern analog building blocks. This course is worth 12 Engineering Design Points.Subjects

circuit | circuit | advanced circuit techniques | advanced circuit techniques | multiplexers | multiplexers | sample-and-holds | sample-and-holds | gain-controlled amplifiers | gain-controlled amplifiers | analog multipliers | analog multipliers | digital-to-analog | digital-to-analog | analog-to-digital | analog-to-digital | power amplifiers | power amplifiers | modern analog | modern analogLicense

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 metadata6.253 Convex Analysis and Optimization (MIT) 6.253 Convex Analysis and Optimization (MIT)

Description

6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an intuitive, highly visual, geometrical approach to the subject. 6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an intuitive, highly visual, geometrical approach to the subject.Subjects

affine hulls | affine hulls | recession cones | recession cones | global minima | global minima | local minima | local minima | optimal solutions | optimal solutions | hyper planes | hyper planes | minimax theory | minimax theory | polyhedral convexity | polyhedral convexity | polyhedral cones | polyhedral cones | polyhedral sets | polyhedral sets | convex analysis | convex analysis | optimization | optimization | convexity | convexity | Lagrange multipliers | Lagrange multipliers | duality | duality | continuous optimization | continuous optimization | saddle point theory | saddle point theory | linear algebra | linear algebra | real analysis | real analysis | convex sets | convex sets | convex functions | convex functions | extreme points | extreme points | subgradients | subgradients | constrained optimization | constrained optimization | directional derivatives | directional derivatives | subdifferentials | subdifferentials | conical approximations | conical approximations | Fritz John optimality | Fritz John optimality | Exact penalty functions | Exact penalty functions | conjugate duality | conjugate duality | conjugate functions | conjugate functions | Fenchel duality | Fenchel duality | exact penalty functions | exact penalty functions | dual computational methods | dual computational 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 metadata16.323 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 LQRLicense

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 metadata18.085 Computational Science and Engineering I (MIT)

Description

This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.Note: This course was previously called "Mathematical Methods for Engineers I".Subjects

linear algebra | networks | Lagrange multipliers | differential equations of equilibrium | Laplace's equation | potential flow | boundary-value problems | Fourier series | discrete Fourier transform | convolutionLicense

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 metadata18.085 Computational Science and Engineering I (MIT)

Description

This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications. Note: This course was previously called "Mathematical Methods for Engineers I."Subjects

linear algebra | networks | Lagrange multipliers | differential equations of equilibrium | Laplace's equation | potential flow | boundary-value problems | Fourier series | discrete Fourier transform | convolutionLicense

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 metadata6.253 Convex Analysis and Optimization (MIT)

Description

6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an intuitive, highly visual, geometrical approach to the subject.Subjects

affine hulls | recession cones | global minima | local minima | optimal solutions | hyper planes | minimax theory | polyhedral convexity | polyhedral cones | polyhedral sets | convex analysis | optimization | convexity | Lagrange multipliers | duality | continuous optimization | saddle point theory | linear algebra | real analysis | convex sets | convex functions | extreme points | subgradients | constrained optimization | directional derivatives | subdifferentials | conical approximations | Fritz John optimality | Exact penalty functions | conjugate duality | conjugate functions | Fenchel duality | exact penalty functions | dual computational 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 metadata18.085 Computational Science and Engineering I (MIT)

Description

This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications. Note: This course was previously called "Mathematical Methods for Engineers I."Subjects

linear algebra | networks | Lagrange multipliers | differential equations of equilibrium | Laplace's equation | potential flow | boundary-value problems | Fourier series | discrete Fourier transform | convolutionLicense

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 metadata6.301 Solid-State Circuits (MIT)

Description

This course covers analog circuit analysis and design, focusing on the tools and methods necessary for the creative design of useful circuits using active devices. The class stresses insight and intuition, applied to the design of transistor circuits and the estimation of their performance. The course concentrates on circuits using the bipolar junction transistor, but the techniques that are studied can be equally applied to circuits using JFETs, MOSFETs, MESFETs, future exotic devices, or even vacuum tubes.Subjects

solid state circuits | analog | circuit | transistor | bipolar junction transistor | JFET | MOSFET | MESFET | vacuum tubes | single-transistor common-emitter amplifier | op amps | multipliers | references | high speed logic | high-frequency analysis | open-circuit time constants | transimpedance amps | translinear circuits | bandgap references | charge control modelLicense

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 metadata18.085 Mathematical Methods for Engineers I (MIT)

Description

This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.Subjects

linear algebra | networks | Lagrange multipliers | differential equations of equilibrium | Laplace's equation | potential flow | boundary-value problems | Fourier series | discrete Fourier transform | convolutionLicense

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 metadata6.331 Advanced Circuit Techniques (MIT)

Description

Following a brief classroom discussion of relevant principles, each student in this course completes the paper design of several advanced circuits such as multiplexers, sample-and-holds, gain-controlled amplifiers, analog multipliers, digital-to-analog or analog-to-digital converters, and power amplifiers. One of each student's designs is presented to the class, and one may be built and evaluated. Associated laboratory assignments emphasize the use of modern analog building blocks. This course is worth 12 Engineering Design Points.Subjects

circuit | advanced circuit techniques | multiplexers | sample-and-holds | gain-controlled amplifiers | analog multipliers | digital-to-analog | analog-to-digital | power amplifiers | modern analogLicense

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 metadata6.331 Advanced Circuit Techniques (MIT)

Description

Following a brief classroom discussion of relevant principles, each student in this course completes the paper design of several advanced circuits such as multiplexers, sample-and-holds, gain-controlled amplifiers, analog multipliers, digital-to-analog or analog-to-digital converters, and power amplifiers. One of each student's designs is presented to the class, and one may be built and evaluated. Associated laboratory assignments emphasize the use of modern analog building blocks. This course is worth 12 Engineering Design Points.Subjects

circuit | advanced circuit techniques | multiplexers | sample-and-holds | gain-controlled amplifiers | analog multipliers | digital-to-analog | analog-to-digital | power amplifiers | modern analogLicense

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 metadata18.085 Mathematical Methods for Engineers I (MIT)

Description

Review of linear algebra, applications to networks, structures, and estimation, Lagrange multipliers, differential equations of equilibrium, Laplace's equation and potential flow, boundary-value problems, minimum principles and calculus of variations, Fourier series, discrete Fourier transform, convolution, applications.Technical RequirementsRealOne Player software is required to run the .rm files found on this course site. MATLAB® is a trademark of The MathWorks, Inc.Subjects

linear algebra | networks | Lagrange multipliers | differential equations of equilibrium | Laplace's equation | potential flow | boundary-value problems | Fourier series | discrete Fourier transform | convolutionLicense

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 metadata15.066J System Optimization and Analysis for Manufacturing (MIT)

Description

One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations management.Subjects

modeling | optimization | simulation | manufacturing systems | decision making | decision support | probabilistic simulation | designing manufacturing systems | operations management | linear programming | sensitivity analysis | network flow problems | non-linear programming | Lagrange multipliers | integer programming | discrete-event simulation | heuristics | algorithms | 15.066 | 2.851 | 3.83License

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 metadata16.323 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.Subjects

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

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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