An Adaptive LQG Combined With the MRAS - Based LFFC for Motion Control Systems
Nguyen Duy Cuong, Nguyen Van Lanh, and Gia Thi Dinh
Electronics Faculty, Thai nguyen University of Technology, Thai nguyen City, Viet nam
Abstract—The aim of this paper is to develop advanced controllers for electromechanical motion systems. A new controller is proposed to take into account the inherent non-linear disturbances, measurement noise, and variations and uncertainties in process behavior. It consists of a Linear Quadratic Gaussian (LQG) controller and a separate supplementary MRAS-based Learning Feed-Forward Controller (LFFC). Instead of design that is based on a fixed mathematical model of the process, the optimal steady-state filter gain L in the Linear Quadratic Estimator (LQE) and the feedback gain K in the Linear Quadratic Regulator (LQR) can be determined based on the parameters of the feed-forward part, which follows continuously the process at different load conditions. This will result in “an adaptive LQG combined with the MRAS-based LFFC”. Simulation results demonstrate the potential benefits of the proposed method.
Index Terms—model reference adaptive systems (MRAS), linear quadratic gaussian (LQG), learning feed-forward control (LFFC), motion control systems
Cite: Nguyen Duy Cuong, Nguyen Van Lanh, and Gia Thi Dinh, "An Adaptive LQG Combined With the MRAS - Based LFFC for Motion Control Systems," Journal of Automation and Control Engineering, Vol. 3, No. 2, pp. 130-136, April, 2015. doi: 10.12720/joace.3.2.130-136
Index Terms—model reference adaptive systems (MRAS), linear quadratic gaussian (LQG), learning feed-forward control (LFFC), motion control systems
Cite: Nguyen Duy Cuong, Nguyen Van Lanh, and Gia Thi Dinh, "An Adaptive LQG Combined With the MRAS - Based LFFC for Motion Control Systems," Journal of Automation and Control Engineering, Vol. 3, No. 2, pp. 130-136, April, 2015. doi: 10.12720/joace.3.2.130-136