Trajectory Tracking Controller Design for a Ball-Plate Balancing System Using ANFIS

The Ball-Plate Balancing (BPB) problem is a widely known nonlinear control problem, and numerous control system solutions have been proposed to solve it. The BPB is a nonlinear system with the under-actuation characteristic that makes control harder to accomplish trajectory tracking objectives. Therefore, in this article, Adaptive Neuro Fuzzy Inference System (ANFIS) based closed loop controller is designed for precise trajectory tracking control objective by the ball, along with the dynamics model of BPB. In addition to the proposed controller, a comparison study is carried out with the existing conventional Proportional Integral and Derivative (PID) controller. In order to validate the proposed ANFIS-based controller, tracking simulations have been conducted using two distinct trajectories: a circular path and a Lissajous pattern.