Reliable Stabilization in T-S Fuzzy Feedback Control System Through Adaptive Lyapunov Function
Iqbal Ahammed, A k (Anjuman Institute of Technology and Management, Bhatkal, Karnataka, India); Mohammed Fazle Azeem (King Khalid University, Saudi Arabia)
In industry, most of the physical systems are nonlinear with different forms. It is often difficult for design and control the nonlinear system. The non-linear systems with dynamic disturbances, which are caused due to modeling errors, measurement noise, external/ internal disturbances, delayed input, etc., will affect the system. To conquer this problem, T-S fuzzy model is designed for efficient management in the control of complex systems. In this paper, we propose a Reliable Takagi-Sugeno fuzzy controller via state feedback and output feedback controller to provide robust stabilization with parameter uncertainty and disturbances. The motivation behind this fuzzy dynamic output feedback controller design guarantees the robust asymptotic stability of the closed-loop system and guarantees a sufficient constraint on disturbance attenuation for every single admissible uncertainty in which the constraints are based on the quadratic affine Lyapunov function approach, which is less conservative than the common Lyapunov function. The stability functions are expressed in the form of Linear Matrix Inequalities. A trial result is abused to illustrate the effectiveness and possibilities of the proposed approach.
Journal: International Journal of Simulation- Systems, Science and Technology- IJSSST V20
Published: Feb 28, 2019