Performance improvement by optimal reset dynamic output feedback control based on model predictive strategy. (April 2020) - Yazdi, Sepide; Khayatian, Alireza
Highlights: A systematic approach for designing a reset dynamic output feedback controller is presented. The D-stability approach is used to design a DOFC for the base system. The after reset value at each reset time is designed by solving an optimization problem based on model prediction strategy. The best times for resetting action are derived by genetic algorithm based on minimizing a multivariable cost function which contains certain transient performances. The merits of the proposed controller are demonstrated by applying it on a continuous stirred tank reactor and a distillation column. Abstract: This paper proposes a systematic approach for designing a reset dynamic output feedback controller (DOFC). The reset controller is designed in three steps. First, the D-stability approach is used to design the gain matrices of the DOFC for the base system such that the poles of the closed-loop system are placed in a predefined region. This region is chosen based on the control objectives. Moreover, the sufficient conditions for existence of base controller are formulated in terms of linear matrix inequalities. Second, the reset times are derived by applying genetic algorithm to minimize a novel cost function of certain transient performances. Third, an optimization problem based on model prediction strategy is solved for finding the after reset value at each reset time. The proposed method is applied to two different systems: continuous stirred tank reactor and distillation column. The effectiveness of the proposed reset controller is shown by comparing the results with other approaches.