Input-Output Feedback Linearization Cascade Controller Using Genetic Algorithm for Rotary Inverted Pendulum System

Abstract

The Rotary Inverted Pendulum (RIP) system is a significant classical problem of control engineering which has been investigated in the past decades. This study presents an optimum Input- Output Feedback Linearization (IOFL) cascade controller utilized Genetic Algorithm (GA). Due to the non-minimum phase behavior of the system, IOFL controller leads to unstable internal dynamics. Therefore a cascade structure is proposed consisting IOFL controller for inner loop with PD controller forming the outer loop. The primary design goal is to balance the pendulum in an inverted position. The control criterion is to minimize the Integral Absolute Error (IAE) of system angles. By minimizing the objective function related to IAE using Binary Genetic Algorithm (BGA), the optimal controller parameters can be assigned. The results verified capability and competent characteristics of the proposed controller. The method can be considered as a promising way for control of various similar nonlinear and under-actuated systems.