ADAPTIVE MODEL PREDICTIVE CONTROL FOR NONLINEAR ELASTIC SERVO DRIVE CONTROL SYSTEMS

The paper presents an approach to designing an adaptive model predictive controller for elastic electrical servo drive systems with uncertain nonlinear parameters. For the synthesis of an adaptive predictive control, extended linearization based on state-dependent coefficient matrices is used to adaptively linearize a nonlinear system at each internal sampling instant during the prediction procedure. For solving the objective function of a predicted model, the quadratic programming optimization algorithm is considered. The next section introduces the mathematical state space model of nonlinear multi-mass elastic servo drive of a large radio telescope control system with taking the backlash and dry Coulomb friction torque into consideration. Finally, the proposed adaptive model predictive controller is tested in simulation of servo position tracking of a large radio telescope (the RT-70 antenna) in comparing with traditional optimal LQR controller. It is shown that the proposed controller can guarantee control system at global asymptotic stability and robustness. In this work, designing and testing of nonlinear model predictive control are implemented on Matlab/SIMULINK environment.

Authors: M. P. Belov, T. H. Phuong , D. V. Thuy

Direction: Electrical Engineering

Keywords: Servo drive system, adaptive model predictive controller, extended linearization, quadratic programming

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