Application of LQG combined with MRAS-based LFFC to Electromechanical Motion Systems

In this paper we introduce a new control structure which consists of a Linear Quadratic Gaussian (LQG) controller and a Model Reference Adaptive System (MRAS)-based Learning Feed-Forward Controller (LFFC) to Electromechanical Motion Systems. Feed-forward is used in addition to LQG because LQG is still required to account for imperfections in the feed-forward system model. By adding a Learning Feed-Forward (LFF) component to the LQG controller, an extra degree of freedom in the controller design is created. The advantages of the proposed method are verified by simulation and experimental results. A control scheme is derived which has good properties in common with both the LQG and LFFC controller. This control structure can capture many aspects of the control problems. The responses to setpoint changes and reproducible disturbances are mainly obtained by the LFFC. The LQG is designed to obtain a stable closed-loop system that is insensitive to measurement noise and variations and uncertainties in process behavior.