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Virtual Reference Feedback Tuning of MIMO Data-Driven Model-Free Adaptive Control Algorithms

Abstract : This paper proposes a new tuning approach by which all Model-Free Adaptive Control (MFAC) algorithm parameters are computed using a nonlinear Virtual Reference Feedback Tuning (VRFT) algorithm. This new mixed data-driven control approach, which results in a mixed data-driven tuning algorithm, is advantageous as it offers a systematic way to tune the parameters of MFAC algorithms by VRFT using only the input/output data of the process. The proposed approach is validated by a set of MIMO experiments conducted on a nonlinear twin rotor aerodynamic system laboratory of equipment position control system. The mixed VRFT-MFAC algorithm is compared with a classical MFAC algorithm whose initial parameter values are optimally tuned.
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Submitted on : Tuesday, January 17, 2017 - 3:37:58 PM
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Raul-Cristian Roman, Mircea-Bogdan Radac, Radu-Emil Precup, Emil Petriu. Virtual Reference Feedback Tuning of MIMO Data-Driven Model-Free Adaptive Control Algorithms. 7th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2016, Costa de Caparica, Portugal. pp.253-260, ⟨10.1007/978-3-319-31165-4_25⟩. ⟨hal-01438250⟩



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