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Robust Control Optimization with Metaheuristics [Kõva köide]

  • Formaat: Hardback, 448 pages, kõrgus x laius x paksus: 236x152x28 mm, kaal: 794 g
  • Ilmumisaeg: 17-Jan-2017
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1786300427
  • ISBN-13: 9781786300423
Teised raamatud teemal:
Robust Control Optimization with MetaheuristicsSuurem pilt
  • Formaat: Hardback, 448 pages, kõrgus x laius x paksus: 236x152x28 mm, kaal: 794 g
  • Ilmumisaeg: 17-Jan-2017
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1786300427
  • ISBN-13: 9781786300423
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781786300423.html
Märksõnad:

In the automotive industry, a Control Engineer must design a unique control law that is then tested and validated on a single prototype with a level of reliability high enough to to meet a number of complex specifications on various systems. In order to do this, the Engineer uses an experimental iterative process (Trial and Error phase) which relies heavily on his or her experience. This book looks to optimise the methods for synthesising servo controllers by making them more direct and thus quicker to design. This is achieved by calculating a final controller to directly tackle the high-end system specs.

Preface ix
Chapter 1 Metaheuristics for Controller Optimization 1(34)
1.1 Introduction
1(1)
1.2 Evolutionary approaches using differential evolution
2(6)
1.2.1 Standard version
2(5)
1.2.2 Perturbed version
7(1)
1.3 Swarm approaches
8(25)
1.3.1 Particle swarm optimization algorithm
8(6)
1.3.2 Quantum particle swarm algorithm
14(6)
1.3.3 Artificial bee colony optimization algorithm
20(5)
1.3.4 Cuckoo search algorithm
25(6)
1.3.5 Firefly algorithm
31(2)
1.4 Summary
33(2)
Chapter 2 Reformulation of Robust Control Problems for Stochastic Optimization 35(136)
2.1 Introduction
35(1)
2.2 synthesis
35(70)
2.2.1 Full Hinfinity synthesis
35(10)
2.2.2 Fixed-structure Hinfinity synthesis
45(22)
2.2.3 Formulating Hinfinity synthesis for stochastic optimization
67(38)
2.2.4 Conclusion
105(1)
2.3 µ-Synthesis
105(35)
2.3.1 The problem of performance robustness
105(5)
2.3.2 µ-Synthesis
110(30)
2.4 LPV/LFT synthesis
140(31)
2.4.1 Introduction
140(1)
2.4.2 The LPV/LFT controller synthesis problem
141(6)
2.4.3 Reformulation for stochastic optimization
147(24)
Chapter 3 Optimal Tuning of Structured and Robust Hinfinity Controllers Against High-level Requirements 171(108)
3.1 Introduction and motivations
171(9)
3.2 Loop-shaping Hinfinity synthesis
180(14)
3.2.1 Approach principle
180(4)
3.2.2 Generalized gain and phase margins
184(1)
3.2.3 Four-block interpretation of the method
185(1)
3.2.4 Practical implementation
186(4)
3.2.5 Implementation of controllers
190(4)
3.3 A generic method for the declination of requirements
194(4)
3.3.1 General principles
194(2)
3.3.2 Special cases
196(1)
3.3.3 Management of requirement priority level
197(1)
3.4 Optimal tuning of weighting functions
198(40)
3.4.1 Optimization on nominal plant
198(4)
3.4.2 Multiple plant optimization
202(5)
3.4.3 Applicative example - inertial stabilization of line of sight
207(31)
3.5 Optimal tuning of the fixed-structure and fixed-order final controller
238(41)
3.5.1 Introduction
238(2)
3.5.2 Toward eliminating weighting functions
240(19)
3.5.3 Extensions to the approach
259(18)
3.5.4 Link with standard control problems
277(2)
Chapter 4 HinfStoch: A Toolbox for Structured and Robust Controller Computation Based on Stochastic Optimization 279(72)
4.1 Introduction
279(1)
4.2 Structured multiple plant Hinfinity synthesis
280(4)
4.2.1 Principle
280(1)
4.2.2 Formalism
280(4)
4.3 Structured µ-synthesis
284(4)
4.3.1 Principle
284(1)
4.3.2 Formalism
285(3)
4.4 Structured LPV/LFT synthesis
288(4)
4.4.1 Principle
288(1)
4.4.2 Formalism
289(3)
4.5 Structured and robust synthesis against high-level requirements with HinfStoch_ControllerTuning
292(59)
4.5.1 Principle
292(1)
4.5.2 Formalism
293(18)
4.5.3 Examples
311(40)
Appendices 351(48)
Appendix A: Notions of Coprime Factorizations
353(6)
Appendix B: Examples of LFT Form Used for Uncertain Systems
359(6)
Appendix C: LFT Form Use of an Electromechanical System with Uncertain Flexible Modes
365(18)
Appendix D: FTM (ID) Computation from a Time Signal
383(2)
Appendix E: Choice of Iteration Number for CompLeib Tests
385(8)
Appendix F: PDE versus DE
393(6)
Bibliography 399(8)
Index 407
Philippe Feyel is an R&D Engineer for the high-tech company Sagem Défense Sécurité, part of the defence and security business of the SAFRAN group, in Paris, France.