Genetic Algorithm–Based Robust Controller for an Inverted Pendulum Using Model Order Reduction

Abstract

Robust stabilization is an important characterization to get improved in the control system to optimize the performance of the desired system. Most of the controllers available suffer from problems such as difficulty in the tuning process, sluggishness in response time, quick and global convergence, etc. This paper considered proportional-integral optimized with genetic algorithm (GA-PID)controller on inverted pendulum for the control of the angle position. A MATLAB script for a GA was developed to obtain optimum PID parameters that would keep the pendulum angle at equilibrium (i.e., returns the pendulum to the desired point as quickly as possible) by minimizing an objective function (integral time absolute error [ITAE]). Furthermore, obtained outcomes confirm the performance of holding on the upright position from the downward direction such that the angle of the pendulum is manipulated to control the inverted position in its erect position in a rapid manner. In the experimental analysis, the developed GA-based PID controller is compared with the conventional PID controller to evaluate the performance of the inverted pendulum. The obtained results show that the GA-based PID controller confirms the enhanced performance indexes by holding minimum settling time and peak overshoot on comparing with the conventional PID controller.

Provide A Method Based on Genetic Algorithm to Optimize the Fuzzy Logic Controller for the Inverted Pendulum

“…The genetic algorithm uses the simple coding method and propagation mechanism to express the complex phenomenon, thus solving the complex problem. In [4], considered proportional-integral optimized with genetic algorithm (GA-PID) controller on inverted pendulum for the control of the angle position. In [15], in order to simultaneously stabilize the both degrees of freedom, a robust sliding mode controller is designed for this under-actuated system.…”

“…One of the classic systems in dynamics and control is inverted pendulum, which is known as one of the topics in control engineering due to its properties such as nonlinearity and inherent instability [3]. Recent research has provided soft computational methods for inverse pendulum controller using adaptive fuzzy neural inference system [4]. The process of the proposed method takes place in four stages.…”