Open Access

ARTICLE

Intelligent Dynamic Inversion Controller Design for Ball and Beam System

Ibrahim M. Mehedi^1,2,*, Abdulah Jeza Aljohani^1,2, Md Mottahir Alam¹, Mohamed Mahmoud³, Mohammed J. Abdulaal¹, Muhammad Bilal^1,2, Waleed Alasmary⁴

1 Department of Electrical and Computer Engineering (ECE), King Abdulaziz University, Jeddah, 21589, Saudi Arabia
2 Center of Excellence in Intelligent Engineering Systems (CEIES), King Abdulaziz University, Jeddah, 21589, Saudi Arabia
3 Electrical and Computer Engineering, Electrical and Computer Engineering, TN, 38505, United States
4 Computer and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia

* Corresponding Author: Ibrahim M. Mehedi. Email:

Computers, Materials & Continua 2022, 72(2), 2341-2355. https://doi.org/10.32604/cmc.2022.022993

Received 25 August 2021; Accepted 20 December 2021; Issue published 29 March 2022

Abstract

The Ball and beam system (BBS) is an attractive laboratory experimental tool because of its inherent nonlinear and open-loop unstable properties. Designing an effective ball and beam system controller is a real challenge for researchers and engineers. In this paper, the control design technique is investigated by using Intelligent Dynamic Inversion (IDI) method for this nonlinear and unstable system. The proposed control law is an enhanced version of conventional Dynamic Inversion control incorporating an intelligent control element in it. The Moore-Penrose Generalized Inverse (MPGI) is used to invert the prescribed constraint dynamics to realize the baseline control law. A sliding mode-based intelligent control element is further augmented with the baseline control to enhance the robustness against uncertainties, nonlinearities, and external disturbances. The semi-global asymptotic stability of IDI control is guaranteed in the sense of Lyapunov. Numerical simulations and laboratory experiments are carried out on this ball and beam physical system to analyze the effectiveness of the controller. In addition to that, comparative analysis of RGDI control with classical Linear Quadratic Regulator and Fractional Order Controller are also presented on the experimental test bench.

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