Developments in Advanced Control and Intelligent Automation for Complex Systems (Studies in Systems, Decision and Control, 329)

✍ Scribed by Min Wu (editor), Witold Pedrycz (editor), Luefeng Chen (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 409
• Category: Library

✦ Synopsis

This book discusses the developments in the advanced control and intelligent automation for complex systems completed over the last two decades, including the progress in advanced control theory and method, intelligent control and decision-making of complex metallurgical processes, intelligent systems and machine learning, intelligent robot systems design and control, and prediction and control technology for renewable energy. With the depth and breadth of coverage of this book, it serves as a useful reference for engineers in the field of automation and complex process control and graduate students interested in advanced control theory and computational intelligence as well as their applications to the complex industrial processes. This book offers an up-to-date overview of this active research area. It provides readers with the state-of-the-art methods for advanced control and intelligent automation for complex systems

✦ Table of Contents

Preface
Contents
Advanced Control Theory and Method
Stability Analysis and Hinfty Control of Time-Delay Systems
1 Introduction
2 Stability Analysis Based on A Relaxed Integral Inequality
2.1 System Description
2.2 A Stability Criterion
2.3 A Numerical Example
3 Hinfty Control Design Based on A Parameter Tuning Method
3.1 Problem Formulation
3.2 Hinfty Performance Based Control Design
3.3 A Numerical Example
4 Load Frequency Control for A Delayed One-Area Power System
4.1 Dynamic Model of the LFC Scheme
4.2 Stability Assessment of PI-Based LFC Schemes
4.3 Design of the SF-Based LFC Scheme
4.4 Case Studies
References
Active Disturbance Rejection in Repetitive Control Systems
1 Introduction
2 Repetitive Control
2.1 Two-Dimensional Property of Repetitive Control
2.2 Modified Repetitive-Control System
3 Equivalent-Input-Disturbance Approach
3.1 Basic Concept of Equivalent Input Disturbance
3.2 Equivalent-Input-Disturbance Estimation
3.3 Analysis of Disturbance Rejection
4 Disturbance Rejection for Repetitive Control System with Time-Varying Nonlinearity
4.1 Analysis and Design of Nonlinear MRCS
4.2 Design Algorithm for Nonlinear MRCS
4.3 Simulation Verification and Analysis
5 Conclusion
References
Intelligent Control of Underactuated Mechanical System
1 Introduction
2 Preparations
3 A Continuous Control Method for Planar Underactuated Manipulator with Passive First Joint
3.1 Continuous Controller Design
3.2 Optimization of Target Angles and Design Parameters
3.3 Simulations
4 A Unified Control Method for Planar Underactuated Manipulator with One Passive Joint
4.1 Trajectory Planning and Parameters Optimization
4.2 Trajectory Tracking Controllers Design
4.3 Simulations
5 Conclusion
References
Finite-Time Fault Detection and Hinfty State Estimation for Markov Jump Systems Under Dynamic Event-Triggered Mechanism
1 Introduction
2 Finite-Time Fault Detection
2.1 Problem Formulation
2.2 Main Results
2.3 Detection Threshold Design
2.4 Numerical Example
3 Finite-Time Hinfty State Estimation
3.1 Problem Formulation
3.2 Main Results
3.3 Numerical Example
4 Conclusion
References
Intelligent Control and Decision-Making of Complex Metallurgical Processes
Intelligent Control of Sintering Process
1 Sintering Process and Characteristics Analysis
1.1 Iron Ore Sintering Process
1.2 Characteristics Analysis for Sintering Process
1.3 Control Objectives
2 Carbon Efficiency Prediction and Optimization
2.1 Carbon Efficiency Hybrid Prediction Model
2.2 Carbon Efficiency Intelligent Optimization
2.3 Experimental Results and Analysis
3 Intelligent Control of Sintering Ignition Based on the Prediction of Ignition Temperature
3.1 Control Requirements and Control Structure
3.2 Prediction Model of Ignition Temperature
3.3 Design of Intelligent Controller
3.4 Experiment and Result Analysis
4 Fuzzy Control of Burn-Through Point Based on the Feature Extraction of Time Series Trend
4.1 Control Requirements and Control Structure
4.2 Feature Extraction of Time Series Trend
4.3 Design of Fuzzy Controller
4.4 Experimental Study and Result Analysis
5 Optimization and Control System of Carbon Efficiency
5.1 Architecture of OCSCE
5.2 Implementation Scheme
6 Conclusion
References
Decision-Making of Burden Distribution for Blast Furnace
1 Analysis of Ironmaking and Burden Distribution
1.1 Ironmaking Process
1.2 Gas Flow and Gas Utilization Rate
1.3 Effect of Burden Distribution
2 Prediction Model of Gas Utilization Rate
2.1 Prediction Model of GUR Based on Chaos Theory
2.2 Prediction Model of GUR Based on Case-Matching
2.3 Prediction Model of GUR Based on Multi-time-Scale
3 Decision-Making Strategy
3.1 Structure of Decision-Making Strategy
3.2 Decision-Making Procedure
3.3 Decision-Making Verification
4 Conclusion
References
Intelligent System and Machine Learning
Granular Computing: Fundamentals and System Modeling
1 Introduction
2 Information Granules and Information Granularity
3 Frameworks of Information Granules
4 Information Granules and Their Two-Phase Development Process
4.1 Clustering as a Prerequisite of Information Granules
4.2 The Principle of Justifiable Granularity
5 Augmentation of the Design Process of Information Granules
6 Symbolic View at Information Granules and Their Symbolic Characterization and Summarization
7 Granular Probes of Spatiotemporal Data
8 Granular Models
8.1 The Concept
8.2 Construction of Granular Models
9 Conclusions
References
Distributed Consensus Control for Nonlinear Multi-agent Systems
1 Introduction
1.1 Background and Related Work
1.2 Preliminaries
2 ADHDP-Based Distributed Consensus Control for MASs
2.1 Problem Formulation
2.2 ADHDP-Based Distributed Consensus Control Method
2.3 Implementation of the ADHDP-Based Distributed Consensus Control Method
2.4 Simulation Results
3 ADP-Based Distributed Model Reference Consensus Control for MASs
3.1 Problem Formulation
3.2 ADP-Based Distributed Model Reference Control Method
3.3 MRAC Scheme for Individual Agent
3.4 Distributed Value Iteration Algorithm
3.5 Simulation Studies
4 Conclusion
References
Stochastic Consensus Control of Multi-agent Systems under General Noises and Delays
1 Introduction
2 Problem Formulation and Preliminary
3 Networks with Additive Noises
3.1 Mean Square Weak Consensus
3.2 Almost Sure Weak Consensus
3.3 Mean Square and Almost Sure Strong Consensus
4 Networks with Additive Noises and Delays
4.1 Mean Square Weak Consensus
4.2 Almost Sure Weak Consensus
4.3 Mean Square and Almost Sure Strong Consensus
5 Simulations
6 Conclusion
References
Multimodal Emotion Recognition and Intention Understanding in Human-Robot Interaction
1 Introduction
1.1 Multimodal Emotion Recognition
1.2 Emotional Intention Understanding
1.3 Emotional Human-Robot Interaction System
1.4 The Structure of the Chapter
2 Multimodal Emotion Feature Extraction
2.1 Regions of Interest based Feature Extraction in Facial Expression
2.2 Sparse Coding-SURF based Feature Extraction in Body Gesture
2.3 FCM based Feature Extraction in the Speech Emotion
3 Multimodal Emotion Recognition
3.1 Softmax Regression based Deep Sparse Autoencoder Network for Facial Emotion Recognition
3.2 Multi-SVM based Dempster-Shafer Theory for Gesture Recognition Using Sparse Coding Feature
3.3 Two-Layer Fuzzy Multiple Random Forest for Speech Emotion Recognition
3.4 Two-stage Fuzzy Fusion based Convolution Neural Network for Dynamic Facial Expression and Speech Emotion Recognition
4 Emotion Intention Understanding
4.1 Three-Layer Weighted Fuzzy Support Vector Regression for Emotion Intention Understanding
4.2 Dynamic Emotion Understanding in Human-Robot Interaction Based on Two-layer Fuzzy SVR-TS Model
5 Experiments and Applications of Emotional Human-Robot Interaction System
5.1 Multimodal Emotional Human-Robot Interaction System
5.2 The Application Experiment of Emotional Human-Robot Interaction System
6 Conclusion
References
Dynamic Multi-objective Optimization for Multi-objective Vehicle Routing Problem with Real-time Traffic Conditions
1 Introduction
2 Background
2.1 Basic Definitions
2.2 Dynamic Multi-objective Optimization Algorithms
3 Multi-objective Vehicle Routing Problem with Real-time Traffic Conditions
3.1 Road Network Topology
3.2 Formulation of MOVRPRTC
4 Offline Optimization and Online Optimization for MOVRPRTC
4.1 Framework of ALSDCMOEA
4.2 Online Optimization
5 Experiment
6 Conclusion
References
Intelligent Robot System Design and Control
Dielectric Elastomer Intelligent Devices for Soft Robots
1 Dynamic Modelling of Dielectric Elastomer Intelligent Actuator (DEIA)
1.1 Introduction
1.2 DEIA Manufacture and Experiment Platform Description
1.3 DEIA Modelling
1.4 Parameter Identification of Dynamic Model
1.5 Model Validation
2 Study of Soft Force and Displacement Intelligent Sensor (SFDIS)
2.1 Introduction
2.2 Experiment System Description
2.3 SFDIS Modelling
2.4 Parameter Identification of Sensing Model
2.5 Model Validation
3 Conclusion
References
Design of a 2-DOF Compliant Micropositioning Stage with Large Workspace
1 Introduction
2 Mechanical Design of XY Stage
2.1 Introduction of Basic Mechanisms
2.2 Propose of XY Stage
3 Static Modeling and Characteristic Analysis
3.1 Modeling of Single Flexure Hinges
3.2 Transform of Compliance Matrix
3.3 Compliance Matrix of Each Part
3.4 Output Compliance Matrix of XY Stage
3.5 Input Compliance of XY Stage
3.6 Amplification Ratio of XY Stage
4 Model Verification with FEA
5 Conclusion
References
Assistive Robots
1 Introduction
2 Human-Body-Motion-Controlled Electric Wheelchair
2.1 Electric Wheelchair with Human-Body-Motion Interface
2.2 Tuning of Gain A
2.3 Experiments
2.4 Conclusion
3 Electric Cart for Maintaining Physical Strength
3.1 Hardware of the Cart System
3.2 Driver-Adapted Selection of Pedal Load and Control System
3.3 Estimation of NLF for the Electric Cart Using EID Approach
3.4 Conclusion
4 Design of Left-Right-Independent Lower-Limb Rehabilitation Machine
4.1 Specification and Mechanism Selection
4.2 System Design
4.3 Preliminary Test of Prototype
4.4 Conclusion
References
Prediction and Control Technology for Renewable Energy
A Short-Term Wind Power Forecasting Method Based on Hybrid-Kernel Least-Squares Support Vector Machine
1 Introduction
2 Forecasting Framework
2.1 Wind Power Decomposition Based on Amplitude-Frequency Characteristic
3 Time Series Forecasting Models for Different Classes
3.1 DirRec Time Series Forecasting Model
3.2 HKLSSVM Time Series Forecasting Model
3.3 Optimized HKLSSVM Time Series Model
4 Experiment Design and Experiment Results
4.1 Experiment Design
4.2 Evaluation Criteria
4.3 Experimental Results
5 Conclusion
References