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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Communication dans un congrès
Luis M. Camarinha-Matos; António J. Falcão; Nazanin Vafaei; Shirin Najdi. 7th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2016, Costa de Caparica, Portugal. IFIP Advances in Information and Communication Technology, AICT-470, pp.253-260, 2016, Technological Innovation for Cyber-Physical Systems. 〈10.1007/978-3-319-31165-4_25〉
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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. Luis M. Camarinha-Matos; António J. Falcão; Nazanin Vafaei; Shirin Najdi. 7th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2016, Costa de Caparica, Portugal. IFIP Advances in Information and Communication Technology, AICT-470, pp.253-260, 2016, Technological Innovation for Cyber-Physical Systems. 〈10.1007/978-3-319-31165-4_25〉. 〈hal-01438250〉

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