Position tracking and balancing control of ball balancer system using intelligent controllers

This paper develops an intelligent control approach for achieving the non-linear control of a two degrees of freedom (2DoF) ball balancer system. The ball balancer system provides an example of an inherently unstable and underactuated electromechanical system that can be used to realise the problem of position tracking and balancing control in robotic systems. Besides, intelligent control takes into consideration the system characteristics and parameters and incorporates the heuristic knowledge and a human logical approach to best train the controller for achieving the desired control task. In this research, the robustness of the intelligent controller is realised by developing an adaptive neuro-fuzzy inference system (ANFIS) which is applied with the ball balancer system to achieve position tracking and balancing control. The numerical simulations are carried out using the first-principles method to perform the system modelling, design, and development of the control strategy for a two-dimensional ball balancer system. The performance of the proposed controller is assessed in terms of the time domain characteristics and a comparative study is done to demonstrate the superiority of intelligent control techniques over classical control techniques.