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LMI-based cooperative distributed model predictive control for Lipschitz nonlinear systems

Adelipour, S ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1002/oca.2553
  3. Publisher: John Wiley and Sons Ltd , 2020
  4. Abstract:
  5. In this paper, a distributed model predictive control is proposed to control Lipschitz nonlinear systems. The cooperative distributed scheme is considered where a global infinite horizon objective function is optimized for each subsystem, exploiting the state and input information of other subsystems. Thus, each control law is obtained separately as a state feedback of all system's states by solving a set of linear matrix inequalities. Due to convexity of the design, convergence properties at each iteration are established. Additionally, the proposed algorithm is modified to optimize only one control input at a time, which leads to a further reduction in the computation load. Finally, two application cases are studied to show the effectiveness of the proposed method. © 2019 John Wiley & Sons, Ltd
  6. Keywords:
  7. Computational load reduction ; Cooperative distributed control ; Distributed computer systems ; Distributed parameter control systems ; Iterative methods ; Linear matrix inequalities ; Nonlinear systems ; State feedback ; Computational loads ; Convergence properties ; Distributed control ; Distributed Model predictive Control ; Distributed schemes ; Infinite horizons ; Lipschitz nonlinear systems ; Objective functions ; Model predictive control
  8. Source: Optimal Control Applications and Methods ; Volume 41, Issue 2 , 2020 , Pages 487-498
  9. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/oca.2553