Particle Swarm Optimization Based LQR Control of an Inverted Pendulum
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Development of new control methods and the improvement of existing control techniques have been interest of researchers for many years. Inverted pendulum systems have been used to test the performance of various control methods in many studies due to their unstable and nonlinear structures. In this work, the use of Particle Swarm Optimization algorithm is presented for the parameter optimization of a Linear Quadratic Regulator controller designed to stabilization and position control of an inverted pendulum. Equations of motion of the cart pendulum derived by Lagrange formulation have been linearized and presented as state-space model. A Linear Quadratic Regulator controller has been designed for position control and stabilization of pendulum system. Parameters of the controller have been optimized by Particle Swarm Optimization algorithm to obtain best control results. Simulation studies were carried out in the MATLAB/Simulink environment and performance of the designed controller has been evaluated through simulation results.
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