An Intelligent Control of an Inverted Pendulum Based on an Adaptive Interval Type-2 Fuzzy Inference System
Ayad Al-Mahturi, Fendy Santoso, Matthew Garratt, Sreenatha Gopalarao Anavatti · 2019
Interval Type-2 fuzzy controllers have become increasingly popular, and have been applied in many engineering applications over the past few decades. In this paper, a knowledge-based interval Type-2 fuzzy controller is proposed to control an inverted pendulum on a cart system in the presence of disturbance, random noise and parameter variations. The proposed controller utilizes the Takagi-Sugeno fuzzy inference system, supported by the Nie-Tan (NT) type-reduction method for the input-output mapping. The adaptation laws for the Type-2 fuzzy consequent parameters are derived based on the sliding mode control (SMC) theory. A comparison study of the proposed interval Type-2 fuzzy controller with a conventional PID controller is investigated in the presence of disturbance, external noise and parameter variations. Simulation results show the efficacy of the proposed controller with respect to a conventional PID controller as indicated by lower RMSE values.