A Study of T–S Model-Based SMC Scheme With Application to Robot Control

Abstract

In light of the remarkable benefits and numerous applications of the Takagi-Sugeno (T-S) fuzzy system modeling method and the sliding mode control (SMC) technique, this paper aims to study the design of robust controllers for a set of second-order systems using a combination of these two approaches. The combined scheme is shown to have the merits of both approaches. It alleviates not only the online computational burden by using the T-S fuzzy system model to approximate the original nonlinear one (since most of the system parameters of the T-S model can be computed offline) but also preserves the advantages of rapid response and robustness characteristic of the classic SMC schemes. Moreover, the combined scheme does not need to online compute any nonlinear term of the original dynamics, and the increase in the number of fuzzy rules does not create extra online computational burdens for the scheme. The proposed analytical results are also applied to the control of a two-link robot manipulator and compared with the results using classic SMC design. Simulation results demonstrate the benefits of the proposed scheme.