In this paper, the problem of hybrid model predictive control(HMPC) strategy based on fuzzy supervisor for piecewise autoregressive with exogenous input(PWARX) models is addressed. We first represent the nonlinear beh...In this paper, the problem of hybrid model predictive control(HMPC) strategy based on fuzzy supervisor for piecewise autoregressive with exogenous input(PWARX) models is addressed. We first represent the nonlinear behavior of the system with a PWARX model. Then, we transform the obtained PWARX model into a mixed logical dynamic(MLD) model in order to apply the proposed predictive control which is able to stabilize such systems along desired reference trajectories while satisfying operating constraints.Finally, we propose to introduce a fuzzy supervisor allowing the readjustment of the HMPC tuning parameters in order to maintain the desired performance. Simulation and experimental results are presented to illustrate the effectiveness of the proposed approach.展开更多
文摘In this paper, the problem of hybrid model predictive control(HMPC) strategy based on fuzzy supervisor for piecewise autoregressive with exogenous input(PWARX) models is addressed. We first represent the nonlinear behavior of the system with a PWARX model. Then, we transform the obtained PWARX model into a mixed logical dynamic(MLD) model in order to apply the proposed predictive control which is able to stabilize such systems along desired reference trajectories while satisfying operating constraints.Finally, we propose to introduce a fuzzy supervisor allowing the readjustment of the HMPC tuning parameters in order to maintain the desired performance. Simulation and experimental results are presented to illustrate the effectiveness of the proposed approach.
