%0 Conference Paper
%A Mani, G.
%A Sivaraman, N.
%A Kannan, R.
%D 2018
%F scholars:9654
%I Institute of Electrical and Electronics Engineers Inc.
%K Balancing; Benchmarking; Controllers; Degrees of freedom (mechanics); Electric control equipment; Proportional control systems; Three term control systems; Time domain analysis; Two term control systems; Visual servoing, Ball balancers; Conventional proportional integrals; Dominant pole placements; MIT rule; Model reference adaptive controllers; Modified MRAC; MRAC; Time-domain specifications, Model reference adaptive control
%R 10.1109/ICIAS.2018.8540635
%T Visual Servoing Based Model Reference Adaptive Control with Lyapunov Rule for a Ball on Plate Balancing System
%U https://khub.utp.edu.my/scholars/9654/
%X The 2 Degree of Freedom (DoF) ball balancer system is a highly nonlinear system where the position of the ball is controlled by controlling the two servo motors simultaneously. In general, conventional Proportional Integral Derivative (PID) controller and Proportional Velocity (PV) is used to control the location of the ball on a plate in X and Y axes. But the major concerns are both classic PID and PV fails to track the ball position accurately due to non-linearity, process parameters variations and uncertainties. The above demerits are overcome by implementing Model Reference Adaptive Controller (MRAC) based PID controller. The closed loop reference model is chosen based on desired time domain specifications and by dominant pole placement technique. The gain values of the PID controller are tuned by MRAC to obtain optimal performance. MRAC based PID controller with MIT rule, modified MRAC with MIT approach, and modified MRAC with the Lyapunov rule are implemented in Simulink. The controller's performance on the benchmark Quanser 2 Dof ball balancer system is evaluated in real-time and comparative analysis is made. From the comparison, it is found modified MRAC based Lyapunov approach suppress the overshoot, provides better stability and tracks the system set-point accurately. On the other hand modified MRAC offers less Root Mean Square (RMS) value and faster tracking with less adaptation gain. © 2018 IEEE.
%Z cited By 1; Conference of 7th International Conference on Intelligent and Advanced System, ICIAS 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:143005