Study on bifurcation analysis and Takagi–Sugeno fuzzy sampled‐data stabilization of permanent magnet synchronous motor systems
Rajarathinam Vadivel, Sabarathinam Srinivasan, Yongbao Wu, Nallappan Gunasekaran · Mathematical Methods in the Applied Sciences · 2021
The bifurcation, stability, and stabilization analysis of permanent magnet synchronous motor (PMSM) systems are investigated in this paper. To begin, a new class of delay‐dependent sufficient conditions are suggested with respect to the information of the membership functions, a relevant Lyapunov–Krasovskii functional (LKF), and the overall information connected with the real sampling pattern, so that the fuzzy system is ensured to be stable with a weighted dissipativity efficiency. Second, a sampled‐data control is intended to stabilize the Takagi–Sugeno (T‐S) fuzzy system with specified integral inequalities based on the obtained results. The required conditions are stated in terms of the linear matrix inequalities (LMIs) under the dissipativity output index and can be verified by MATLAB toolbox. Finally, verification examples are contributed to demonstrate the efficacy of the techniques established in this paper.