UID:
almahu_9949501730402882
Format:
1 online resource :
,
illustrations
Edition:
First edition.
ISBN:
9781003160700
,
1003160700
,
9781000860290
,
1000860299
,
9781000860276
,
1000860272
Content:
"One of the main problems in science and engineering is to provide a quantitative description of the systems under investigation, leveraging collected noisy data. Such a description may be a complete mathematical model or a mechanism to return controllers corresponding to new, unseen inputs. Recent advances in the theories are described in detail, along with their applications in engineering. The book aims to develop model-free system analysis and control strategies, i.e., data-driven control from theoretical analysis and engineering applications based only on measured data. The study aims to develop system identification, and combination in advanced control theory, i.e., data-driven control strategy as system and controller are generated from measured data directly. The book covers the development of system identification and its combination in advanced control theory, i.e., data-driven control strategy, as they all depend on measured data. Firstly, data-driven identification is developed for the closed-loop, nonlinear system and model validation, i.e., obtaining model descriptions from measured data. Secondly, the data-driven idea is combined with some control strategies to be considered data-driven control strategies, such as data-driven model predictive control, data-driven iterative tuning control, and data-driven subspace predictive control. Thirdly data-driven identification and data-driven control strategies are applied to interested engineering. In this context, the book provides algorithms to perform state estimation of dynamical systems from noisy data and some convex optimization algorithms through identification and control problems"--
Note:
Introduction. Data driven model predictive control. Data driven identification for closed loop system. Data driven model validation for closed loop system. Data driven identification for nonlinear system. Data driven iterative tuning control. Data driven applications. Data driven subspace prediction control. Conclusions and outlook.
Additional Edition:
ISBN 9780367746599
Additional Edition:
ISBN 036774659X
Additional Edition:
ISBN 9780367750084
Additional Edition:
ISBN 0367750082
Language:
English
DOI:
10.1201/9781003160700
URL:
https://www.taylorfrancis.com/books/9781003160700
