Advanced control engineering

Chapter 1 Introduction to Control Engineering00

1.1 Introduction00

1.2 Historical Review00

1.3 Development of Control Theory00

1.4 Control Strategies00

1.5 Control System Fundamentals00

1.6 Examples of Control Systems0

Chapter 2 Modeling of Dynamic Systems0

2.1 Introduction0

2.2 Differential Equation0

2.3 Transfer Function0

2.4 Block Diagrams0

2.5 Stateª²Space Model0

2.6 Timeª²Domain Analysis of Control System0

Chapter 3 Optimal Control0

3.1 Introduction0

3.2 Typical Optimal Control Problems and Solutions0

3.3 Fundamentals of Optimal Control0

3.4 Linear Quadratic Regulator0

3.5 Kalman Filter0

3.6 Linear Quadratic Gaussian Control System0

3.7 Optimal Control Examples0

Chapter 4 Model Predictive Control0

4.1 Introduction0

4.2 MPC Control Problem0

4.3 Key Aspects of MPC0

4.4 Programming of MPC0

4.5 A Study on EEGª²Based Vehicle Control with MPC Controller0

4.6 Recommendation on Control Parameters of MPC0

Chapter 5 Sliding Mode Control

5.1 Introduction

5.2 Definition of Sliding Mode Control

5.3 Basic Problems in SMC Design

5.4 Characteristics and Mathematical Description of Sliding Mode

5.5 Sliding Mode Control Design

5.6 Chattering

5.7 Control Examples

5.8 A Study on Brainª²Controlled Mobile Robots

Chapter 6 Artificial Neural Network Control

6.1 Introduction

6.2 Fundamentals of Artificial Neural Network

6.3 Property of Neural Network

6.4 The Structure £¨Architecture£© of Artificial Neural Network

6.5 Activation Function

6.6 Learning in Neural Network

6.7 Generalization

6.8 Selected Types of Neural Network

Chapter 7 Fuzzy Logic Control Systems

7.1 Introduction

7.2 Fuzzy Sets

7.3 Fuzzy Inference

7.4 Fuzzy Control

7.5 Self Organizing Fuzzy Logic Control £¨SOFLC£©

7.6 Application of Fuzzy Controllers

Chapter 8 Neuroª²Fuzzy Control Systems

8.1 Introduction

8.2 Types of Neuroª²Fuzzy Systems

8.3 General Architecture of Neuroª²Fuzzy Systems

8.4 Various Architecture of Neuroª²Fuzzy Models

8.5 Learning in Neuroª²Fuzzy Systems

8.6 Selected Neuroª²Fuzzy Systems

Chapter 9 Genetic Algorithm for Control Systems

9.1 Introduction

9.2 GA Optimization Process

9.3 Binary Representation and Real Representation

9.4 Selection Operator

9.5 Genetic Operators for Binary Representation

9.6 Genetic Operators for Real Representation

9.7 Control Examples with Genetic Algorithm

Chapter 10 Reinforcement Learning Control

10.1 Introduction

10.2 Fundamentals of Reinforcement Learning

10.3 Markov Decision Process

10.4 Dynamic Programming for Finite MDP

10.5 Model Learning for MDP

10.6 Continuous State MDP

10.7 Qª²Learning of Temporal Difference Control

10.8 Control Example with Reinforcement Learning