A novel adaptive neuro linear quadratic regulator (ANLQR) controller design on DC‐DC buck converter

This paper proposes an Adaptive Neuro Linear Quadratic Regulator (ANLQR) controller for Buck converter operating under harmful disturbances. Considering the real-time condition of a with regular variations, Neural Network is adopted to improve and tune gain LQR strategy adaptive mechanism. assumes system as Gray-box process without need exact mathematical model which can result in lower computational burden, faster dynamics, ease implementation. ANLQR control suitable alternative considering its significant robustness against different disturbances, particularly noise. It should be mentioned that number neurons limited 2 4 each layer decrease burden complexity. The advantages this method justified various situations through experimental simulation outcomes. Moreover, PSO-PID controllers are designed compared presented carry on comparison proposed method. Furthermore, approach provides better outcomes dynamics frequency adaption environments.