Adaptive MPC based on MIMO ARX-Laguerre model. (March 2017) - Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais
Abstract: This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Abstract : Highlights: Analytical solution of optimal MIMO ARX-Laguerre model is proposed. A recursive algorithm of Fourier coefficients estimation is developed. A new approach of the online identification of MIMO ARX-Laguerre model is given. Adaptive predictive control strategy of MIMO systems is proposed.