Common applications using fuzzy models are warming, aerating and cooling system, ventilating, robot, warm exchange pilot plant and wheel inverted pendulum. In these areas, the correct selection of fuzzy tenets is important in T-S Fuzzy model to control the system, which gives strength and nature of the system. T-S model can accurately rough the non-linear system and the steadiness. Fuzzy logic hypothesis is one of the control techniques and it is the efficient approach to manage the uncertainty issue for complex nonlinear system. A fuzzy controller utilizes fuzzy standards such as though then proclamations including fuzzy logic, fuzzy sets and fuzzy interference. One of the fuzzy systems is Takagi-Sugeno (T-S) fuzzy model is an effective device in approximating most complex non-linear system. The T-S models the non-linear system by weighted whole of linear time invariant systems.

Papers:

Li, Hongyi, Lijie Wang, Haiping Du, and Abdesselem Boulkroune, “Adaptive fuzzy backstepping tracking control for strict-feedback systems with input delay,” IEEE Transactions on Fuzzy Systems, vol. 25, no. 3, 2017, pp. 642-652

Ding Zhai, An-Yang Lu a, Jiuxiang Dong b, Qing-Ling Zhang a, “Stability analysis and state feedback control of continuous-time T–S fuzzy systems via anew switched fuzzy Lyapunov function approach,” Applied Mathematics and Computation, vol. 293, 2017, pp. 586–599.

Yan-Jun Liu, Shaocheng Tong, Dong-Juan Li and Ying Gao, “Fuzzy Adaptive Control with State Observer for a Class of Nonlinear Discrete-Time Systems with Input Constraint,” IEEE transaction on fuzzy systems, 2015.

Hongyi Li, Jiahui Wang and Peng Shi, “Output-Feedback Based Sliding Mode Control for Fuzzy Systems with Actuator Saturation,” IEEE Transaction on Fuzzy systems, 2015.