Research article

Designing and tuning MIMO feedforward controllers using iterated LMI restriction


  • Received: 29 December 2021 Revised: 18 April 2022 Accepted: 25 April 2022 Published: 29 April 2022
  • In this paper, a multi-input multi-output (MIMO) feedforward control structure is proposed and designed based on the linear matrix inequality (LMI) approach to improve disturbance rejection and reference tracking of the given feedback system. The proposed architecture consists of two MIMO feedforward controllers, where each controller can be designed independently using the proposed method. The unknown variables of the feedforward controllers are calculated using LMI restrictions such that the H-norm of the transfer function matrix from disturbance (set-point) to output (error) is minimized. By taking advantage of the frequency sampling techniques and using some iterative algorithms, convergence of the solution to a local optimal point is guaranteed. For solving this optimization problem the CVX optimization tool is used and the numerical results are presented. The proposed method can be considered as a new tractable approach for tuning the parameters of MIMO feedforward controllers.

    Citation: Saeedreza Tofighi, Farshad Merrikh-Bayat, Farhad Bayat. Designing and tuning MIMO feedforward controllers using iterated LMI restriction[J]. Electronic Research Archive, 2022, 30(7): 2465-2486. doi: 10.3934/era.2022126

    Related Papers:

  • In this paper, a multi-input multi-output (MIMO) feedforward control structure is proposed and designed based on the linear matrix inequality (LMI) approach to improve disturbance rejection and reference tracking of the given feedback system. The proposed architecture consists of two MIMO feedforward controllers, where each controller can be designed independently using the proposed method. The unknown variables of the feedforward controllers are calculated using LMI restrictions such that the H-norm of the transfer function matrix from disturbance (set-point) to output (error) is minimized. By taking advantage of the frequency sampling techniques and using some iterative algorithms, convergence of the solution to a local optimal point is guaranteed. For solving this optimization problem the CVX optimization tool is used and the numerical results are presented. The proposed method can be considered as a new tractable approach for tuning the parameters of MIMO feedforward controllers.



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