| 紀錄類型: |
書目-電子資源
: Monograph/item
|
| 正題名/作者: |
Advanced control systems/ Yuriy P. Kondratenko ... [et al.], editors. |
| 其他題名: |
theory and applications / |
| 其他作者: |
Kondratenko, Yuriy P. |
| 出版者: |
Gistrup, Denmark :River Publishers, : 2021., |
| 面頁冊數: |
1 online resource (478 p.) :ill. |
| 內容註: |
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of 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 the Presence of Pulse Perturbations -- 1.5 Conclusion -- 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 -- 3: Principle of Time Stretching for Motion Control in Condition of Conflict -- 3.1 Introduction -- 3.2 Equivalence of the Pursuit Game with Delay of Information 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 -- 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. |
| 內容註: |
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 -- 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 -- 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. |
| 內容註: |
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 -- 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 -- 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 -- 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 -- 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. |
| 內容註: |
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 -- 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 -- 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 -- 13: Intelligent Algorithms for the Automation of Complex Biotechnical Objects -- 13.1 Introduction. |
| 內容註: |
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 -- 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 -- Index -- About the Editors. |
| 標題: |
Automatic control. - |
| 電子資源: |
https://www.taylorfrancis.com/books/9781003337010 |
| ISBN: |
9781003337010 |