Ant Colony Based LQR and PID tuned Parameters for Controlling Inverted Pendulum

This paper presents an optimization technique to adjust the LQR and PID controller parameters to control the nonlinear plant of inverted pendulum using the integral square error (ISE) as an objective function. The system is modeled in the state space representation. The control task is to move the cart of the inverted pendulum to a desired point and stabilize the angle of the pendulum at the vertical position. An LQR controller is used in the state feedback along with the PID controller. The parameters of both the PID controller and the LQR state feedback controller are tuned using Ant Colony Optimization (ACO) algorithm. The simulation of the control problem has been designed using MATLAB Simulink and MATLAB script code. The results show that Ant Colony Optimization (ACO) algorithm is efficient in tuning the parameters to give the optimum response. It is obviously seen that the integral square error (ISE) does not exceed 0.03 when using the proposed design approach.