Constrained output tracking control for time varying bilinear systems via RHC with infinite prediction horizon

The paper introduces an algorithm to design a feedback controller, which guarantees the tracking of time varying bilinear system outputs for desired values in the presence of input constraint. The proposed controller employs the ideas of receding horizon principle and constrained optimal control. | Journal of Computer Science and Cybernetics, , (2015), 97–106 DOI: CONSTRAINED OUTPUT TRACKING CONTROL FOR TIME-VARYING BILINEAR SYSTEMS VIA RHC WITH INFINITE PREDICTION HORIZON NGUYEN DOAN PHUOC1 AND LE THI THU HA2 1 Hanoi University of Science and Technology; 2 Thai Nguyen University of Technology; hahien1977@ Abstract. The paper introduces an algorithm to design a feedback controller, which guarantees the tracking of time varying bilinear system outputs for desired values in the presence of input constraint. The proposed controller employs the ideas of receding horizon principle and constrained optimal control. A theorem for the tracking stability of closed loop system is given. An updated law of weighting matrices in the cost function to keep the input constraint condition is also proposed. Finally, the tracking behavior of the closed loop system is illustrated through a numerical example. Keywords. Receding horizon control, constrained nonlinear optimization, dynamic programming, output tracking control. 1. INTRODUCTION The problem of output tracking control for nonlinear systems in the presence of constraints is known as an interesting problem of control theory, which has attracted the attention of many control researchers for a long time, but still has not been fully investigated so far. This control problem is attractive since the obtained tracking controller can take into account the limitation of actuators through the input and state constraints, restrict the overshoot of system states as well, and hence prevent damages to system components. Unfortunately, this problem has still not been fully studied due to very large classes of nonlinear systems. Therefore, to effectively solve the problem, a certain class of nonlinear systems as good representative of others should be determined. One of such class is bilinear systems since the bilinear model is the most natural form to .

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