Digital control and state variable methods : conventional and intelligent control systems

Description

Cover Contents Part I Digital Control: Principles and Design in Transform Domain 1. Introduction 1.1 Control System Terminology 1.2 Computer-Based Control: History and Trends 1.3 Control Theory: History and Trends 1.4 An Overview of the C lassical Approach to Analog Controller Design 2. Signal Processing in Digital Control 2.1 Why Use Digital Control? 2.2 Configuration of the Basic Digital Control Scheme 2.3 Principles of Signal Conversion 2.4 Basic Discrete-Time Signals 2.5 Time-Domain Models for Discrete-Time Systems 2.6 The z-Transform 2.7 Transfer Function Models 2.8 Frequency Response 2.9 Stability on the z-Plane and the Jury Stability Criterion 2.10 Sample-and-Hold Systems 2.11 Sampled Spectra and Aliasing 2.12 Reconstruction of Analog Signals 2.13 Practical Aspects of the Choice of Sampling Rate 2.14 Principles of Discretization Review Examples Problems 3. Models of Digital Control Devices and Systems 3.1 Introduction 3.2 z-Domain Description of Sampled Continuous-Time Plants 3.3 Z-Domain Description of Systems with Dead-Time 3.4 Implementation of Digital Controllers 3.5 Tunable PID Controllers 3.6 Digital Temperature Control System 3.7 Digital Position Control System 3.8 Stepping Motors and Their Control 3.9 Programmable Logic Controllers Review Examples Problems 4. Design of Digital Control Algorithms 4.1 Introduction 4.2 z-Plane Specifications of Control System Design 4.3 Digital Compensator Design using Frequency Response Plots 4.4 Digital Compensator Design using Root Locus Plots 4.5 z-Plane Synthesis Review Examples Problems Part II State Variable Methods in Automatic Control: Continuous-Time and Sampled-Data Systems 5. Control System Analysis Using State Variable Methods 5.1 Introduction 5.2 Vectors and Matrices 5.3 State Variable Representation 5.4 Conversion of State Variable Models to Transfer Functions 5.5 Conversion of Transfer Functions to Canonical State Variable Models 5.6 Eigenvalues and Eigenvectors 5.7 Solution of State Equations 5.8 Concepts of Controllability and Observability 5.9 Equivalence Between Transfer Function and State Variable Representations 5.10 Multivariable Systems Review Examples Problems 6. State Variable Analysis of Digital Control Systems 6.1 Introduction 6.2 State Descriptions of Digital Processors 6.3 State Description of Sampled Continuous-Time Plants 6.4 State Description of Systems with Dead-Time 6.5 Solution of State Difference Equations 6.6 Controllability and Observability 6.7 Multivariable Systems Review Examples Problems 7. Pole-Placement Design and State Observers 7.1 Introduction 7.2 Stability Improvement by State Feedback 7.3 Necessary and Sufficient Conditions for Arbitrary Pole-Placement 7.4 State Regulator Design 7.5 Design of State Observers 7.6 Compensator Design by the Separation Principle 7.7 Servo Design: Introduction of the Reference Input by Feedfor ward Control 7.8 State Feedback with Integral Control 7.9 Digital Control Systems with State Feedback 7.10 Deadbeat Control by State Feedback and Deadbeat Observers Review Examples Problems 8. Linear Quadratic Optimal Control through Lyapunov Synthesis 8.1 Introduction 8.2 The Concept of Lyapunov Stability 8.3 Lyapunov Functions for Linear Systems 8.4 Parameter Optimization and Optimal Control Problems 8.5 Quadratic Performance Index 8.6 Control Configurations 8.7 Optimal State Regulator 8.8 Optimal Digital Control Systems 8.9 Constrained State Feedback Control Review Examples Problems Part III Nonlinear Control Systems: Conventional and Intelligent 9. Nonlinear Systems Analysis 9.1 Introduction 9.2 Some Common Nonlinear System Behaviors 9.3 Common Nonlinearities in Control Systems 9.4 Describing Function Fundamentals 9.5 Describing Functions of Common Nonlinearities 9.6 Stability Analysis by the Describing Function Method 9.7 Concepts of Phase-Plane Analysis 9.8 Construction of Phase Portraits 9.9 System Analysis on the Phase Plane 9.10 Simple Variable Structure Systems 9.11 Lyapunov Stability Definitions 9.12 Lyapunov Stability Theorems 9.13 Lyapunov Functions for Nonlinear Systems 9.14 Lypunov’s Linearization Method and Local Stability Review Examples Problems 10. Nonlinear Control Structures 10.1 Introduction 10.2 Feedback Linearization 10.3 Model Reference Adaptive Control 10.4 System Identification and Generalized Predictive Control in Self-Tuning Mode 10.5 Sliding Mode Control Problems 11. Intelligent Control with Neural Networks/Support Vector Machines 11.1 Towards Intelligent Systems 11.2 Introduction to Soft Computing and Intelligent Control Systems 11.3 Basics of Machine Learning 11.4 A Brief History of Neural Networks 11.5 Neuron Models 11.6 Network Architectures 11.7 Function Approximation with Neural Networks 11.8 Linear Learning Machines 11.9 Training The Multilayer Perceptron Network–Backpropagation Algorithm 11.10 Radial Basis Function Networks 11.11 System Identification with Neural Networks 11.12 Control with Neural Networks 11.13 Support Vector Machines Review Examples Problems 12. Fuzzy Logic and Neuro-Fuzzy Systems 12.1 Introduction 12.2 Fuzzy Rules-Based Learning 12.3 Fuzzy Quantification of Knowledge 12.4 Fuzzy Inference 12.5 Designing A Fuzzy Logic Controller (Mamdani Architecture) 12.6 Data Based Fuzzy Modeling (Sugeno Architecture) 12.7 System Identification and Control with Neuro-Fuzzy Systems Review Examples Problems 13. Optimization with Genetic Algorithms 13.1 Evolutionary Algorithms 13.2 Genetic Algorithms 13.3 Genetic-Fuzzy Systems 13.4 Genetic-Neural Systems Review Examples Problems 14. Intelligent Control with Reinforcement Learning 14.1 Introduction 14.2 Elements of Reinforcement Learning Control 14.3 Methods for Solving the Reinforcement Learning Problem 14.4 Basics of Dynamic Programming 14.5 Temporal Difference Learning 14.6 Q-Learning 14.7 Sarsa-Learning References Answers to Problems Index