Boyd S., Barratt C. Linear Controller Design. Limits of Perfomance 1991 torrent

Textbook in PDF format

The main topic of the book is closed-loop design and the computation of performance limits using convexity. The book introduces a standard framework for the control design problem and describes many practical design specifications in this framework. It is shown that many of these specifications are closed-loop convex; the corresponding control design problems can therefore be cast as infinite-dimensional nondifferentiable convex optimization problems. The book shows how these problems can be solved using the ellipsoid and cutting-plane algorithms, using a Ritz approximation.
The book describes how the achievable performance can be computed numerically for any family of closed-loop convex specifications. Closed-loop convex specifications include, for example, H-two, H-infinity, or l-one norm bounds, entropy bounds, step response envelopes and asymptotic command decoupling.
The book contains many previously unpublished results. The clear exposition and numerous examples make the material accessible to a wide audience, including researchers, graduate students and industrial control engineers. The book includes standalone chapters covering norms of signals and systems, and their computation, as well as standalone chapters covering convex analysis and nondifferentiable convex optimization.
Control Engineering and Controller Design.
Overview of Control Engineering.
Goals of Controller Design.
Control Engineering and Technology.
Purpose of this Book.
Book Outline.
Notes and References.
A framework for controller design.
A Framework for Control System Architecture.
Terminology and Definitions.
Assumptions.
Some Standard Examples from Classical Control.
A Standard Numerical Example.
A State-Space Formulation.
Notes and References.
Controller Design Specifications and Approaches.
Design Specifications.
The Feasibility Problem.
Families of Design Specifications.
Functional Inequality Specifications.
Multicriterion Optimization.
Optimal Controller Paradigm.
General Design Procedures.
Notes and References.
Analytical tools.
Norms of Signals.
Definition.
Common Norms of Scalar Signals.
Common Norms of Vector Signals.
Comparing Norms.
Notes and References.
Norms of Systems.
Paradigms for System Norms.
Norms of SISO LTI Systems.
Norms of MIMO LTI Systems.
Important Properties of Gains.
Comparing Norms.
State-Space Methods for Computing Norms.
Notes and References.
Geometry of Design Specifications.
Design Specifications as Sets.
Affine and Convex Sets and Functionals.
Closed-Lo op Convex Design Specifications.
Some Examples.
Implications for Tradeoffs and Optimization.
Convexity and Duality.
Notes and References.
Design specifications.
Realizability and Closed-Loop Stability.
Realizability.
Internal Stability.
Modified Controller Paradigm.
A State-Space Parametrization.
Some Generalizations of Closed-Lo op Stability.
Notes and References.
Performance Specifications.
Input/Output Specifications.
Regulation Specifications.
Actuator Effort.
Combined Effect of Disturbances and Commands.
Differential Sensitivity Specifications.
Bode's Log Sensitivities.
MAMS Log Sensitivity.
General Differential Sensitivity.
Notes and References.
Robustness Specifications via Gain Bounds.
Robustness Specifications.
Examples of Robustness Specifications.
Perturbation Feedback Form.
Small Gain Method for Robust Stability.
Small Gain Method for Robust Performance.
Notes and References.
A Pictorial Example.
I/O Specifications.
Regulation.
Actuator Effort.
Sensitivity Specifications.
Robustness Specifications.
Nonconvex Design Specifications.
A Weighted-Max Functional.
Notes and References.
Numerical methods.
Some Analytic Solutions.
Linear Quadratic Regulator.
Linear Quadratic Gaussian Regulator.
Minimum Entropy Regulator.
A Simple Rise Time, Undershoot Example.
A Weighted Peak Tracking Error Example.
Notes and References.
Elements of Convex Analysis.
Subgradients.
Supporting Hyperplanes.
Tools for Computing Subgradients.
Computing Subgradients.
Subgradients on a Finite-Dimensional Subspace.
Notes and References.
Special Algorithms for Convex Optimization.
Notation and Problem Definitions.
On Algorithms for Convex Optimization.
Cutting-Plane Algorithms.
Ellipsoid Algorithms.
Example: LQG Weight Selection via Duality.
Complexity of Convex Optimization.
Notes and References.
Solving the Controller Design Problem.
Ritz Approximations.
An Example with an Analytic Solution.
An Example with no Analytic Solution.
An Outer Approximation via Duality.
Some Tradeoff Curves.
Notes and References.
Discussion and Conclusions.
The Main Points.
Control Engineering Revisited.
Some History of the Main Ideas.
Some Extensions.
Notation and Symbols.
List of Acronyms