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Practical Explicit Model Predictive Control for a Class of Noise-embedded Chaotic Hybrid Systems
Seyyed Mostafa Tabatabaei,Sara Kamali,Mohammad Reza Jahed Motlagh,Mojtaba Barkhordari Yazdi 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.4
Controlling a class of chaotic hybrid systems in the presence of noise is investigated in this paper. Toreach this goal, an explicit model predictive control (eMPC) in combination with nonlinear estimators is employed. Using the eMPC method, all the computations of the common MPC approach are moved off-line. Therefore, theoff-line control law makes it easier to be implemented in comparison with the on-line approach, especially forcomplex systems like the chaotic ones. In order to verify the proposed control structure practically, an op-ampbased Chua’s chaotic circuit is designed. The white Gaussian noise is considered in this circuit. Therefore, thenonlinear estimators –extended and unscented Kalman filter (EKF and UKF)– are utilized to estimate signals fromthe noise-embedded chaotic system. Performance of these estimators for this experimental setup is compared inboth open-loop and closed-loop systems. The experimental results demonstrate the effectiveness of the eMPCapproach as well as the nonlinear estimators for chaos control in the presence of noise.