Comparative Analysis Between Fuzzy Logic Control, LQR Control with Kalman Filter and PID Control for a Two Wheeled Inverted Pendulum

Abstract

The aim of this article is to make a comparison between the performance of a fuzzy logic controller (FLC) and two linear controllers: a classical PID and a LQR with Kalman filter when they are applied to the two-wheeled mobile inverted pendulum robot InstaBot SRAT-2. The research is focused on determining the best controller for the mobile platform using three different performance indexes: (i) the standard deviation of the tilt angle, (ii) the root mean square value of the signal sent to the electrical motors and (iii) the region of convergence of the tilt angle. From the experimental test was observed that the LQR with Kalman filter controller presents a lower energy consumption and lower standard deviation of the error with respect to the PID controller; however the fuzzy controller presents a greater region of convergence than the two linear controllers. From the performance indexes it was concluded that fuzzy control is best suited for the mobile robot InstaBot SRAT-2.