LQR Control Implementation in Simulink
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Implementation of Linear Quadratic Regulator (LQR) control using Simulink.
LQR control is a widely used method that designs controllers by optimizing a linear quadratic cost function. In Simulink, this can be achieved using the LQR Controller block, which computes the optimal gain matrix K solving the algebraic Riccati equation. The block provides parameter tuning options for adjusting state weighting matrix Q and control weighting matrix R according to system requirements. Key implementation steps include defining system state-space matrices, specifying Q and R matrices based on performance priorities, and connecting the LQR block to the plant model. Through Simulink simulations, engineers can evaluate controller performance metrics such as settling time, overshoot, and stability margins, then iteratively refine the design by adjusting weighting matrices or adding integral action for steady-state error elimination.
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