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| موضوع: كتاب Stochastic Distribution Control System Design الأحد 21 يونيو 2020, 12:02 am | |
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أخوانى فى الله أحضرت لكم كتاب Stochastic Distribution Control System Design A Convex Optimization Approach Lei Guo , Hong Wang
و المحتوى كما يلي :
Contents 1 Developments in Stochastic Distribution Control Systems . 1 1.1 Introduction . 1 1.1.1 Paper Web Formation Systems . 3 1.1.2 Flame Distribution Control 4 1.1.3 Challenging Issues . 6 1.2 Stochastic Distribution Control when Output PDFs are Measurable . 8 1.3 Stochastic Distribution Control when Output PDFs are Unmeasurable . 11 1.4 Minimum Entropy Control . 12 1.5 Stochastic Distribution Filtering Design 13 1.6 Conclusions . 14 Part I Structural Controller Design for Stochastic Distribution Control Systems 2 Proportional Integral Derivative Control for Continuous-time Stochastic Systems . 17 2.1 Introduction . 17 2.2 Problem Formulation . 18 2.2.1 Model Representation 18 2.2.2 Pseudo-PID Controller Structure . 19 2.3 Pseudo-PID Controller Design 21 2.3.1 Solvability Condition . 21 2.3.2 Feasible Design Procedures 23 2.3.3 Robust Pseudo-PID Controller . 26 2.4 Simulations . 27 2.5 Conclusions . 29 3 Constrained Continuous-time Proportional Integral Derivative Control Based on Convex Algorithms . 31 3.1 Introduction . 31 xiiiContents 3.2 Problem Formulation . 32 3.2.1 B-spline Expansion and Dynamic Weight Model 32 3.2.2 Generalized PID Controller Design . 34 3.3 Constrained PID Controller Design Based on LMIs 35 3.3.1 Peak-to-peak Performance Control 35 3.3.2 Peak-to-peak Tracking Performance 38 3.3.3 Peak-to-peak Constrained Tracking Control 40 3.4 Simulations . 41 3.5 Conclusions . 42 4 Constrained Discrete-time Proportional Integral Control Based on Convex Algorithms . 45 4.1 Introduction . 45 4.2 Problem Formulation . 45 4.2.1 B-spline Expansion and Discrete-time Weight Dynamical Model 45 4.2.2 Target Weight Model and Discrete-time PI Controller 47 4.3 Robust Constrained Tracking Control 48 4.3.1 Solvability for Peak-to-peak Performance 48 4.3.2 Peak-to-peak Tracking Performance 51 4.3.3 Constrained Peak-to-peak Tracking Control 53 4.4 Simulations . 54 4.5 Conclusions . 55 Part II Two-step Intelligent Optimization Modeling and Control for Stochastic Distribution Control Systems 5 Adaptive Tracking Stochastic Distribution Control for Two-step Neural Network Models . 63 5.1 Introduction . 63 5.2 Output PDF Model Using B-spline Neural Network 64 5.3 Dynamic Neural Network Identification 65 5.4 Adaptive Tracking Control for Weight Reference Model 68 5.5 Illustrative Examples 71 5.5.1 Example 1 71 5.5.2 Example 2 72 5.6 Conclusions . 76 6 Constrained Adaptive Proportional Integral Tracking Control for Two-step Neural Network Models with Delays . 81 6.1 Introduction . 81 6.2 Output PDF Model Using B-spline Neural Network 82 6.3 Time Delay DNNs Identification 83 6.4 Constrained PI Tracking Control for Weight Vector 87 6.5 Illustrative Examples 91 6.5.1 Example 1 91 xivContents 6.5.2 Example 2 93 6.6 Conclusions . 97 7 Constrained Proportional Integral Tracking Control for Takagi-Sugeno Fuzzy Model . 101 7.1 Introduction . 101 7.2 Problem Statement and Preliminaries 101 7.2.1 Output PDF Model Using B-spline Expansion 101 7.2.2 PI Controller Design Based on T-S Fuzzy Model 103 7.3 Main Results 104 7.3.1 Stability Analysis with L1 Measure Index 104 7.3.2 Peak-to-peak Tracking Performance 106 7.3.3 Constrained Peak-to-peak Tracking Control 108 7.4 An Illustrative Example . 109 7.5 Conclusions . 110 Part III Statistical Tracking Control – Driven by Output Statistical Information Set 8 Multiple-objective Statistical Tracking Control Based on Linear Matrix Inequalities . 115 8.1 Introduction . 115 8.2 Problem Formulation and Preliminaries 115 8.3 Formulation for the H2/H? Tracking Problem 117 8.4 Illustrative Examples 122 8.5 Conclusions . 125 9 Adaptive Statistical Tracking Control Based on Two-step Neural Networks with Time Delays . 129 9.1 Introduction . 129 9.2 Problem Formulation and Preliminaries 129 9.3 Time Delay DNNs Identification 130 9.4 Variable Structure Tracking Control for Weight Vectors . 132 9.5 An Illustrative Example . 136 9.6 Conclusions . 138 Part IV Fault Detection and Diagnosis for Stochastic Distribution Control Systems 10 Optimal Continuous-time Fault Detection Filtering 145 10.1 Introduction . 145 10.2 Problem Formulation . 146 10.3 Main Result . 147 10.4 Numerical Examples 152 10.5 Conclusions . 155 xvxvi Contents 11 Optimal Discrete-time Fault Detection and Diagnosis Filtering 157 11.1 Introduction . 157 11.2 Formulation of the FDD Problem with Guaranteed Cost Performance158 11.3 The Optimal Fault Detection Filter Design . 160 11.4 Fault Diagnosis Filter Design . 162 11.5 Simulation Examples . 165 11.6 Conclusions . 166 Part V Conclusions 12 Summary and Potential Applications . 173 12.1 Summary . 173 12.2 Potential Applications of PDF Control . 174 12.2.1 PDF Control in Data-driven Modeling . 174 12.2.2 PDF Control in Data Dimension Reduction 175 12.2.3 PDF Control in Multi-scale Plant-wide Modeling for Fault Diagnosis and Fault Tolerant Control 175 References . 179 Index . 193
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