tailieunhanh - Output feedback control with constraints for nonlinear systems via piecewise quadratic optimization

The paper proposes a nonlinear control method, which can be applied to output tracking control a wide range of various perturbed nonlinear objects. This output feedback controller is established based on piecewise quadratic optimizing subjected to input constraints for state feedback control and then combined with an appropriate EKF or UKF for system state observation. | Vietnam Journal of Science and Technology 55 (3) (2017) 324-333 DOI: OUTPUT FEEDBACK CONTROL WITH CONSTRAINTS FOR NONLINEAR SYSTEMS VIA PIECEWISE QUADRATIC OPTIMIZATION Nguyen Doan Phuoc1, *, Pham Van Hung2, Hoang Duc Quynh3 1 Hanoi University of Science and Technology, 1 Dai Co Viet, Hanoi 2 3 Hanoi University of Industry, 298 Cau Dien, Hanoi Thai Nguyen Industrial Economic-Technology College, Trung Thanh, Pho Yen, Thai Nguyen * Email: Received: 13 July 2016; Accepted for publication: 8 February 2017 ABSTRACT Very few output feedback control methods can be applied for a large class of nonlinear objects. If the control problem has supplementary constraints to satisfy, the number of suitable methods will be fewer. The paper proposes a nonlinear control method, which can be applied to output tracking control a wide range of various perturbed nonlinear objects. This output feedback controller is established based on piecewise quadratic optimizing subjected to input constraints for state feedback control and then combined with an appropriate EKF or UKF for system state observation. The simulation results obtained by applying this proposed controller to output tracking control inverted pendulum and boiler-turbine unit had confirmed its promising applicability in practice. Keywords: quadratic optimization, EKF/UKF filtering, optimal control. 1. INTRODUCTION Whereas almost nonlinear control methods are unable to handle unavoidable system constraints, the MPC method proposed in [1] seems to be a good controller for such constrained control problem. However, since the directly using nonlinear model for output prediction, this technique for NMPC requires additionally a penalty function for objective function in order to guarantee the stability of the closed system [2]. Unfortunately, the question how to choose this penalty function suitably is still open. To overcome this circumstance, the piecewise .

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