| Description |
1 online resource (363 p.) |
| Contents |
Cover -- Title Page -- Copyright Page -- Acknowledgments -- Preface -- Table of Contents -- 1. Introduction of Data Driven Strategy -- 1.1 Introduction -- 1.2 Outline -- 1.3 Contributions -- 2. Data Driven Model Predictive Control -- 2.1 Introduction -- 2.2 Application of bounded error identification into model predictive control -- 2.3 Application of interval predictor model into model predictive control -- 2.4 Stability analysis in cooperative distributed model predictive control -- 2.5 Summary -- 3. Data Driven Identification for Closed Loop System -- 3.1 Introduction |
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3.2 Stealth identification strategy for closed loop linear time invariant system -- 3.3 Performance analysis of closed loop system with a tailor made parameterization -- 3.4 Minimum variance control strategy for the closed loop system -- 3.5 Synthesis identification analysis for closed loop system -- 3.6 Summary -- 4. Data Driven Model Validation for Closed Loop System -- 4.1 Introduction -- 4.2 Model structure validation for closed loop system identification -- 4.3 Non-asymptotic confidence regions in closed loop model validation -- 4.4 Further results on model structure validation |
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4.5 Finite sample properties for closed loop identification -- 4.6 Summary -- 5. Data Driven Identification for Nonlinear System -- 5.1 Introduction -- 5.2 Parallel distributed estimation for polynomial nonlinear state space models -- 5.3 Recursive least squares identification for piecewise affine Hammerstein models -- 5.4 Summary -- 6. Data Driven Iterative Tuning Control -- 6.1 Introduction -- 6.2 Zonotope parameter identification for piecewise affine system -- 6.3 Iterative correlation tuning control for closed loop linear time invariant system |
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6.4 Controller design for many variables closed loop system under non-interaction condition -- 6.5 One improvement on zonotope guaranteed parameter estimation -- 6.6 Summary -- 7. Data Driven Applications -- 7.1 Introduction -- 7.2 Applying set membership strategy in state of charge estimation for Lithium-ion battery -- 7.3 Optimal input signal design for aircraft flutter model parameters identification -- 7.4 Synthesis cascade estimation for aircraft system identification -- 7.5 Summary -- 8. Data Driven Subspace Predictive Control -- 8.1 Introduction |
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8.2 Nearest neighbor gradient algorithm in subspace predictive control under fault condition -- 8.3 Subspace data driven control for linear parameter varying system -- 8.4 Local polynomial method for frequency response function identification -- 8.5 Conclusion -- 9. Conclusions and Outlook -- 9.1 Introduction -- 9.2 Outlook -- Index |
| Summary |
Finding exciting and efficient ways to integrate data into control theory has been a problem of great interest. As most of the classical contributions in control strategy rely on model description, the issue of finding such a model from measured data, i.e., system identification, has become mature research filed |
| Notes |
Description based upon print version of record |
| Form |
Electronic book
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| Author |
Ramirez-Mendoza, Ricardo A
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Morales-Menendez, Ruben
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| ISBN |
9781000860290 |
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1000860299 |
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