Modeling and controller design of an inverted pendulum system using AI approach

Abstract

This project presents the simulation study of few different control approaches that consist of modern controller and intelligent controller for an inverted pendulum system. Inverted pendulum is a nonlinear and unstable dynamic system, which continually moves toward an uncontrolled state. It consists of a cart, driven by a force that can move along a horizontal track, and a pendulum attached to the cart which can rotate freely in the vertical plane parallel to the track. The control problem is to drive the pendulum to its upright position and remains it there as well as maintaining the position of the cart. It involves the derivation of the mathematical modeling that includes the linearization of the model in order to be used with the linear controller. The work follows with designing linear quadric regulator (LQR) as modern controller; fuzzy logic and adaptive neural network fuzzy for the intelligent controller. The simulation of controllers has been done in MATLAB, and their performance is analyzed and compared which is based on common criteria’s of the step response. Overall, LQR controller has the fastest response, whereas adaptive neural network fuzzy controller gives more flexibility in control action