Advanced Control Systems – Theory and Applications
- Length: 300 pages
- Edition: 1
- Language: English
- Publisher: River Publishers
- Publication Date: 2021-08-30
- ISBN-10: 8770223416
- ISBN-13: 9788770223416
- Sales Rank: #0 (See Top 100 Books)
Advanced Control Systems: Theory and Applications provides an overview of advanced research lines in control systems as well as in design, development and implementation methodologies for perspective control systems and their components in different areas of industrial and special applications.
Front Cover Advanced Control Systems: Theory and Applications Contents Preface List of Contributors List of Figures List of Tables List of Abbreviations I Advances in Theoretical Research on Automatic Control 1 On Descriptor Control Impulsive Delay Systems that Arise in Lumped-Distributed Circuits 1.1 Introduction 1.2 Example of Descriptor Control System 1.3 Restrictions, Definitions, and States of System 1.4 A Nonlinear Circuit with Transmission Lines in thePresence of Pulse Perturbations 1.5 Conclusion References 2 An Extremal Routing Problem with Constraints and Complicated Cost Functions 2.1 Introduction 2.2 General Notions and Designations 2.3 General Routing Problem and Its Specific Variant 2.4 Dynamic Programming, 1 2.5 Dynamic Programming, 2 2.6 Computational Experiment 2.7 Conclusion 2.8 Acknowledgment References 3 Principle of Time Stretching for Motion Control in Condition of Conflict 3.1 Introduction 3.2 Equivalence of the Pursuit Game with Delay ofInformation to the Game with Complete Information 3.3 Principle of Time Stretching in Dynamic Games of Pursuit 3.4 Integro-Differential Game of Pursuit 3.5 Illustrative Example of the Integro-Differential Game of Pursuit 3.6 Soft Meeting of Mathematical Pendulums 3.7 Conclusion References 4 Bio-Inspired Algorithms for Optimization of Fuzzy Control Systems: Comparative Analysis 4.1 Introduction 4.2 Related Works and Problem Statement 4.3 Bio-inspired Algorithms of Synthesis and Optimization of Rule Bases for Fuzzy Control Systems 4.3.1 ACO Algorithm for Synthesis and Optimization of Rule Bases for the Mamdani-Type FACS 4.3.2 Genetic Algorithm for Synthesis and Optimization of Rule Bases for the Mamdani-Type FACS 4.3.3 Algorithm of Automatic Rule Base Synthesis for the Mamdani-Type FACS Based on Sequential Search 4.4 Development of the Rule Base of the Fuzzy ControlSystem for the Multipurpose Mobile Robot 4.5 Conclusion References 5 Inverse Model Approach to Disturbance Rejection Problem 5.1 Introduction 5.2 Disturbance Rejection via Inverse Model Control 5.2.1 Inverse Model Control Principle 5.2.2 Inverse Model Design 5.2.3 Inverse Model Based Feedforward Control 5.2.4 Inverse Model Based Disturbance Observer 5.2.5 Disturbance Decoupling Compensator Design 5.3 Sliding Mode Inverse Model Control 5.3.1 Sliding Mode Equivalence Principle 5.3.2 Variable Structure Feedforward Compensator 5.3.3 Variable Structure Disturbance Observer 5.4 Discrete Inverse Model Control 5.4.1 Problem Statement 5.4.2 Discrete Disturbance Observer 5.4.3 Disturbance Observer Parameterization 5.4.4 Disturbance Compensator Structural Synthesis 5.4.5 Disturbance Compensator Parametric Synthesis 5.5 Conclusion References 6 Invariant Relations in the Theory of Optimally Controlled Systems 6.1 Introduction 6.2 The Problems of Price–Target Invariance in the Theory of Optimal Control 6.3 The Problems of Using Singular Controls in Rocket Flight Mechanics 6.3.1 Power Consumption in Degeneracy of the Optimal Control of Rocket Thrust in Atmosphere 6.3.2 Necessary Conditions for the Optimality of a Singular Control 6.3.3 The Problem of Calculating Optimal Trajectories With Singular Arcs 6.4 Addition to the Feldbaum Theorem on Number of Switching 6.5 Investigation of the Invariance in the Modeling of Functioning in Living Nature 6.5.1 Statement of the Anokhin Problem 6.5.2 Solution of the Anokhin Problem 6.5.3 Features of Expediently Functioning Objects with Redundant Control 6.5.4 Structure of the Controlling System of an Expediently Functioning Object 6.5.5 Hierarchy and Invariance of Expediently Controlled System 6.6 Investigation Analysis of Results 6.6.1 Mathematical Modeling – A Tool for Research of Complex Systems 6.6.2 Optimality and Evolution Selection 6.6.3 Hierarchy and Invariance of Expediently Controlled System 6.7 Optimal Control Theory as a Tool for Cognition 6.8 Is Teleology Theological? 6.9 Acknowledgment References 7 Robust Adaptive Controls for a Class of Nonsquare Memoryless Systems 7.1 Introduction 7.2 Problem Formulation 7.3 Background on Pseudoinverse Model-Based Method 7.4 Robust Adaptive Pseudoinverse Model-Based Controllers for SIMO systems 7.5 Robust Adaptive Pseudoinverse Model-Based Control of MIMO System 7.6 Conclusion References II Advances in Control Systems Applications 8 Advanced Identification of Impulse Processes in Cognitive Maps 8.1 Introduction 8.2 Problem Statement 8.3 CM Identification Features 8.4 Subspace Identification with Regularization 8.4.1 Identification for Given Model Dimension 8.4.2 Model Dimension Determination 8.5 Advanced Subspace Identification 8.6 Example 8.7 Conclusion References 9 Strategy for Simulation Complex Hierarchical Systems Based on the Methodologies of Foresight and Cognitive Modeling 9.1 Introduction 9.2 Theoretical Foundation of Foresight and Cognitive Modeling Methodologies 9.2.1 Foresight Methodology of Complex System 9.2.2 Methodology of Cognitive Modeling of Complex Systems 9.2.3 Relationship of the Education System with the Socio-Economic Environment 9.3 Conclusion 9.4 Acknowledgment References 10 Special Cases in Determining the Spacecraft Position and Attitude Using Computer Vision System 10.1 Introduction 10.2 PnP Problem Statement 10.3 PnP Problem Under Uncertainty 10.4 Rotation Parameterization 10.5 Sensitivity of Image 10.6 Estimating an Indistinguishable Set 10.7 Design of Experiment 10.8 Numerical Simulations 10.9 Conclusion References 11 On Determining the Spacecraft Orientation by Information from a System of Stellar Sensors 11.1 Introduction 11.2 Systems of Coordinates: Formulation of the Problem 11.3 Correspondence of Three-Dimensional and Four-Dimensional Parameters of a Group of Three-Dimensional Rotations 11.4 Algorithms for Determining the Orientation Parameters of the Spacecraft 11.5 Accuracy Analysis of Determining the Parameters of the SC Orientation 11.6 Effect of Satellite Initial Orientation Error on the Accuracy of Determining Its Current Orientation 11.7 Conclusion References 12 Control Synthesis of Rotational and Spatial Spacecraft Motion at ApproachingStage of Docking 12.1 Introduction 12.2 Equation of the Spacecraft Relative Motion in the Docking Stage 12.2.1 Equation of the Relative Motion of the Spacecraft Center of Mass 12.2.2 Equation of the Spacecraft Relative Angular Motion 12.2.3 Control Problem Statement at the Docking Stage 12.3 Parameter Estimation of the PSC Rotational Motion 12.3.1 Problem Statement of the Angular Motion Parameters Estimation 12.3.2 Non-Linear Ellipsoidal Estimation Method 12.3.3 Estimation of the Quaternion, Angular Velocity, and Ratios of Inertia Moments 12.3.4 Numerical Simulation of the Estimation Algorithm 12.4 Synthesis of Spacecraft Motion Control at Docking 12.4.1 Synthesis of Motion Control of the Center of Mass of Active Spacecraft 12.4.2 Synthesis of Spacecraft Angular Motion Control 12.4.3 Computer Simulation of Control Algorithm 12.5 Conclusion References 13 Intelligent Algorithms for the Automation of Complex Biotechnical Objects 13.1 Introduction 13.2 Intelligent Automation Systems for Biotechnical Facilities 13.2.1 Traditional Automation Systems for Biotechnical Facilities and their Drawbacks 13.2.2 Synthesis of an Intelligent Control System Taking into Account the Forecasting of the Changes in Temperature Images in the Context of a Poultry House 13.2.3 Synthesis of the Intelligent Control System Taking into Account the Forecast of the External Natural Disturbances and Radiation in the Context of a Greenhouse 13.2.3.1 The Neural Network Forecasting of the External Natural Disturbances 13.2.3.2 The Intelligent Solar Radiation Forecasting System 13.3 Conclusion References 14 Automatic Control for theSlow Pyrolysis of Organic Materials with Variable Composition 14.1 Introduction 14.2 Controlled Pyrolysis Model and Method 14.2.1 Problem Definition 14.2.2 Purpose and Objectives of the Research 14.2.3 Method of Problem Solving 14.2.3.1 Facility Scheme Selection 14.2.3.2 Control Object Model 14.2.3.3 Analysis of the Control Object Model to Solve the Control Task 14.2.3.4 Results of Pyrolysis Product Output Modeling 14.3 Synthesis of the Plant Control System to Produce Product-Gas 14.3.1 The Control Method of Pyrolysis Technology in the Plant 14.3.2 A Simulation Model of the Pyrolysis Plant Control System 14.3.3 Modeling Results of the Control Process by Pyrolysis Installation 14.4 Results and Discussion 14.5 Conclusion References Index About the Editors Back Cover
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