Design and implementation of sliding mode controller for nonlinear systems

Abstract

Sliding Mode Controller (SMC) is the nonlinear controller which is insensitive to unknown disturbances, modeling and parametric uncertainties. Selection of appropriate sliding surface and control law facilitates SMC to control the nonlinear systems effectively. In this research, SMC-PID (Proportional Integral Derivative) and SMC are the two control strategies adopted to bring out the effective performance of nonlinear systems against uncertainties. The nonlinear systems taken in this present work are Magnetic Levitation System (MLS) and ball and beam System. SMC-PID control strategy is designed for MLS and SMC is designed for ball and beam system. To substantiate the performance of SMC-PID for MLS, PID controller is considered as the basic control methodology to be compared with. The efficiency of proposed controller strategy is revealed by conducting various tests such as servo response tracking, disturbance rejection tracking, set point tracking and square wave tracking. The essential parameters such as overshoot, offset, rise time, settling time, Integral Square Error (ISE) and Integral Absolute Error (IAE) are analyzed from various tests and the insensitiveness of the controller against uncertainties are verified. The positive outcomes of the experiments are Overshoot/offset reductions: 70% to 76.7% and 100% reduction in servo response for MLS and ball and beam system respectively. Rise time reductions: Rise time is flat for all tests in ball and beam system. Settling time reductions: For servo response, 33% to 50% reductions in magnetic levitation system and 80% reductions for set point tracking in ball and beam system. ISE reductions: For servo response, 62% to 78% reductions for MLS IAE reductions: For servo response, 81% to 86% reductions in MLS The verified performance outcomes recommend the implementation of SMC-PID and SMC in real time processes of the manufacturing industries and industrial systems. There is a scope for enhancing the simulation response rationally to address the real time facts and constraints. Exploitation of the advanced mathematical techniques and computational algorithms aids to enhance the simulation responses. newline