Real-time control of ball balancer using neural integrated fuzzy controller

This paper presents the design, control, and validation of two degrees of freedom Ball Balancer system. The ball and plate system is a nonlinear, electromechanical, multivariable, closed-loop unstable system on which study is carried out to control the position of ball and plate angle. The model of the system is developed using MATLAB/Simulink, and neural integrated fuzzy and its hybridization with PID have been implemented. The performance of each controller is evaluated in terms of time response analysis and steady-state error. Comparative study of simulation and real-time control results show that by using the neural integrated fuzzy controller and neural integrated fuzzy with proportional-integral-derivative Controller, the peak overshoot is reduced as compared with the PID controller and lead the system prone to appropriate balancing. These control techniques provide a stable and controlled output to the system for ball balancing and plate angle control.