LEADER 12391nam 22007215 450 001 9910484586103321 005 20260126111137.0 010 $a3-030-62147-2 024 7 $a10.1007/978-3-030-62147-6 035 $a(CKB)4100000011807111 035 $a(MiAaPQ)EBC6531695 035 $a(Au-PeEL)EBL6531695 035 $a(OCoLC)1244535728 035 $a(PPN)254722415 035 $a(DE-He213)978-3-030-62147-6 035 $a(EXLCZ)994100000011807111 100 $a20210326d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDevelopments in Advanced Control and Intelligent Automation for Complex Systems /$fedited by Min Wu, Witold Pedrycz, Luefeng Chen 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (x, 411 pages) $cillustrations 225 1 $aStudies in Systems, Decision and Control,$x2198-4190 ;$v329 311 1 $a3-030-62146-4 320 $aIncludes bibliographical references and index. 327 $aIntro -- 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. 327 $aFinite-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. 327 $a2.1 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. 327 $a3 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. 327 $aDynamic 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. 327 $a2.4 Conclusion. 330 $aThis book discusses the developments in the advanced control and intelligent automation for complex systems completed over the last two decades, including the progress in advanced control theory and method, intelligent control and decision-making of complex metallurgical processes, intelligent systems and machine learning, intelligent robot systems design and control, and prediction and control technology for renewable energy. With the depth and breadth of coverage of this book, it serves as a useful reference for engineers in the field of automation and complex process control and graduate students interested in advanced control theory and computational intelligence as well as their applications to the complex industrial processes. This book offers an up-to-date overview of this active research area. It provides readers with the state-of-the-art methods for advanced control and intelligent automation for complex systems. 410 0$aStudies in Systems, Decision and Control,$x2198-4190 ;$v329 606 $aAutomatic control 606 $aRobotics 606 $aAutomation 606 $aControl and Systems Theory 606 $aControl, Robotics, Automation 606 $aControl automàtic$2thub 606 $aRobòtica$2thub 608 $aLlibres electrònics$2thub 615 0$aAutomatic control. 615 0$aRobotics. 615 0$aAutomation. 615 14$aControl and Systems Theory. 615 24$aControl, Robotics, Automation. 615 7$aControl automàtic 615 7$aRobòtica 676 $a629.8 702 $aWu$b Min 702 $aPedrycz$b Witold$f1953- 702 $aChen$b Luefeng 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484586103321 996 $aDevelopments in advanced control and intelligent automation for complex systems$92854448 997 $aUNINA