Intelligent Control and Automation

This book covers different topics from intelligent control and automation, including intelligent control methods, fuzzy control techniques, neural networks-based control, and intelligent control applications. Section 1 focuses on intelligent control methods, describing automatic intelligent control system based on intelligent control algorithm, intelligent multi-agent based information management methods to direct complex industrial systems, a design method of intelligent ropeway type line changing robot based on lifting force control and synovial film controller, and a summary of PID control algorithms based on AI-enabled embedded systems. Section 2 focuses on fuzzy control techniques, describing an adaptive fuzzy sliding mode control scheme for robotic systems, an adaptive backstepping fuzzy control based on type-2 fuzzy system, a fuzzy PID control for respiratory systems, a parameter varying PD control for fuzzy servo mechanism, and a robust fuzzy tracking control scheme for robotic manipulators with experimental verification. Section 3 focuses on neural networks-based control, describing neural network supervision control strategy for inverted pendulum tracking control, a neural PID control strategy for networked process control, a control loop sensor calibration using neural networks for robotic control, a feedforward nonlinear control using neural gas network, and a stable adaptive neural control of a robot arm. Section 4 focuses on intelligent control applications, describing ship steering control based on quantum neural network, a human-simulating intelligent PID control, an intelligent situational control of small turbojet engines, and a technical review of an antilock-braking systems (ABS) control. Cover Title Page Copyright DECLARATION ABOUT THE EDITOR TABLE OF CONTENTS List of Contributors List of Abbreviations Preface Section 1: Intelligent Control Methods Chapter 1 Automatic Intelligent Control System Based on Intelligent Control Algorithm Abstract Introduction Related Work Vector Control Based on Intelligent Control Algorithm Automatic Intelligent Control System Based on Intelligent Control Algorithm Conclusion References Chapter 2 Intelligent Multi-Agent Based Information Management Methods to Direct Complex Industrial Systems Abstract Introduction Current Industrial Systems Architecture IAS and Mass in Industrial Systems Mass: Approches and Algorithms Hybrid Systems: A Case Study Conclusion References Chapter 3 Design Method of Intelligent Ropeway Type Line Changing Robot Based on Lifting Force Control and Synovial Film Controller Abstract Introduction Related Work The Proposed Method Experiment and Analysis Conclusion Acknowledgments References Chapter 4 A Summary of PID Control Algorithms Based on AI-Enabled Embedded Systems Abstract Introduction Basic Principles of PID Classification of PID Control Comparisons of Key Algorithms for PID Control Conclusion References Chapter 5 An Adaptive Fuzzy Sliding Mode Control Scheme for Robotic Systems Abstract Introduction Sliding Mode Control (SMC) Design Decoupled Robot Tracking Control Design Simulation Results Conclusions Appendix A References Section 2: Fuzzy Control Techniques Chapter 6 Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System Abstract Introduction Problem Formulation Interval Type-2 Fuzzy Logic Systems Adaptive Backstepping Fuzzy Controller Design Using IT2FLS Simulation Conclusion Acknowledgment References Chapter 7 Fuzzy PID Control for Respiratory Systems Abstract Introduction Mathematical Model of Respiratory Systems Controller Design System’s Simulations and Results Conclusion Acknowledgments References Chapter 8 A Parameter Varying PD Control for Fuzzy Servo Mechanism Abstract Introduction Motivation for Fuzzy Control Problem Description and Methodology Modelling and Implementation Simulation Results Conclusion References Section 3: Neural Networks-based Control Chapter 9 Neural Network Supervision Control Strategy for Inverted Pendulum Tracking Control Abstract Introduction Control Objective Neural Network Supervision Control Design Simulation Studies Conclusions Acknowledgments References Chapter 10 Neural PID Control Strategy for Networked Process Control Abstract Introduction Stochastic Characteristics of NCS in Operation Processes Design of an NCS Controller Case Studies: Air-Pressure Tank Conclusions Acknowledgments References Chapter 11 Control Loop Sensor Calibration Using Neural Networks for Robotic Control Abstract Introduction Recalibration Approach Control Example I Control Example II Conclusion References Chapter 12 Feedforward Nonlinear Control Using Neural Gas Network Abstract Introduction Neural Gas Approach Plant Model Local Linear Control By State Feedback Experimental Testing Conclusions References Section 4: Intelligent Control Applications Chapter 13 Ship Steering Control Based on Quantum Neural Network Abstract Introduction IASV Mathematical Model QNN Steering Controller Design Simulations and Analysis Conclusions Acknowledgments References Chapter 14 Human-Simulating Intelligent PID Control Abstract Introduction Human-Simulating Pid Control Law Tuning Controller Example and Simulation Conclusions References Chapter 15 Intelligent Situational Control of Small Turbojet Engines Abstract Introduction Situational Control Methodology Framework Design A Small Turbojet Engine: An Experimental Object Situational Control System for A Small Turbojet Engine Experimental Evaluation of the Designed Control System Conclusions Nomenclature Acknowledgments References Chapter 16 An Antilock-Braking Systems (ABS) Control: A Technical Review Abstract Introduction Principles of Antilock-Brake System ABS Control Conclusions Acknowledgement References Index Back Cover