Design of optimized interval type-2 fuzzy logic controller based on the continuity, monotonicity, and smoothness properties for a cart-pole inverted pendulum system

Abstract

In this study, an interval type-2 fuzzy logic controller design method is proposed and validated on the real-time under-actuated nonlinear inverted pendulum system for swing-up and stabilization control problems. The swing-up algorithm is designed to give a faster response and the stabilization controller is designed based on continuity, monotonicity, and smoothness theorems for worst and best cases using the Mamdani fuzzy inference system in order to show the effectiveness of the proposed method. Outstanding type reduction methods are analyzed for the stabilization controller based on the design approach to determine the best type reduction algorithm for the effective and robust control performance. Real-time experiments are conducted to investigate the capability of the proposed controller in terms of adaptation performance and robustness ability. The controller also is able to handle structured and unstructured uncertainties such as measurement noise, external payload, undesirable internal/external disturbances, and parameter uncertainties. The results show that the proposed method clearly improves the control performance of the system in six experimental tasks conducted.

Adaptive control of a class of uncertain nonlinear systems using brain emotional learning and Legendre polynomials

“…In the field of intelligent control, various versions have been presented. Adaptive fuzzy controllers are very popular among intelligent controllers and many researches in this field have been conducted (Kelekci et al, 2022; Mawlani and Arbabtafti, 2022; Zaare and Soltanpour, 2022). The universal approximation property is the main common feature of these researches.…”