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.
Author(s): Jovan Pehcevski
Publisher: Arcler Press
Year: 2022
Language: English
Pages: 422
City: Boston
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
