Simulation for Optimal Control of Nonlinear Inverted Pendulum Dynamical System using PID Controller & LQR

This paper presents the modelling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using Proportional-Integral-Derivative (PID) controller and Linear Quadratic Regulator (LQR). LQR, an optimal control technique, and PID control method, both of which are generally used for control of the linear dynamical systems have been used in this paper to control the nonlinear dynamical system. The nonlinear system states are fed to LQR which is designed using linear state-space model. Inverted pendulum, a highly nonlinear unstable system is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches at a desired position and the inverted pendulum stabilizes in upright position. The MATLAB-SIMULINK models have been developed for simulation of control schemes. The simulation results justify the comparative advantages of LQR control methods. Keywords—Inverted pendulum; nonlinear system; PID control; optimal control; LQR

[1]  M. A. Abido Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization , 2002, IEEE Power Engineering Review.

[2]  Gong Xiao Design of Power System Stabilizers Using Adaptive Chaos Particle Swarm Optimization Algorithm , 2012 .

[3]  Katsuhiko Ogata,et al.  Modern Control Engineering , 1970 .

[4]  P. Antsaklis Intelligent control , 1986, IEEE Control Systems Magazine.

[5]  Chin-Wang Tao,et al.  Fuzzy hierarchical swing-up and sliding position controller for the inverted pendulum-cart system , 2008, Fuzzy Sets Syst..

[6]  T. I. Liu,et al.  Intelligent control of dynamic systems , 1993 .

[7]  Yanmei Liu,et al.  Real-time controlling of inverted pendulum by fuzzy logic , 2009, 2009 IEEE International Conference on Automation and Logistics.

[8]  Amit Patra,et al.  Swing-up and stabilization of a cart-pendulum system under restricted cart track length , 2002, Syst. Control. Lett..

[9]  F. Palis,et al.  Modeling and control of non-linear systems using soft computing techniques , 2007, Appl. Soft Comput..

[10]  Katsuhisa Furuta,et al.  Swinging up a pendulum by energy control , 1996, Autom..

[11]  C. Ibáñez,et al.  Lyapunov-Based Controller for the Inverted Pendulum Cart System , 2005 .

[12]  Raktim Bhattacharya,et al.  Linear quadratic regulation of systems with stochastic parameter uncertainties , 2009, Autom..

[13]  Victor M. Becerra,et al.  Optimal control , 2008, Scholarpedia.

[14]  Tariq Samad,et al.  Intelligent optimal control with dynamic neural networks , 2003, Neural Networks.