In this study, a robust finite time Takagi-Sugeno fuzzy control method for hydro-turbine governing system (HTGS) is investigated. Firstly, the mathematical model of HTGS is introduced, and on the basis of Takagi-Sugeno (T-S) fuzzy rules, the T-S fuzzy model of HTGS is presented. Secondly, based on finite time stability theory, a novel finite time Takagi-Sugeno fuzzy control method is designed for the stability control of HTGS. Thirdly, the relatively loose sufficient stability condition is acquired, which could be transformed into a group of linear matrix inequalities (LMIs) via Schur complement as well as the strict mathematical derivation is given. Furthermore, the control method could resist random disturbances, which shows the good robustness. Simulation results indicate the designed finite time T-S fuzzy control scheme works well compared with the conventional method. The approach proposed in this paper is easy to implement and also provides reference for relevant hydropower systems.

A novel fractional order Takagi–Sugeno (T–S) fuzzy control method for a class of fractional order non‐linear systems is proposed in this study. On the basis of the fractional order interval theory, the generalised T–S fuzzy model for a class of uncertain fractional order non‐linear systems is presented. By using fractional order Lyapunov stability theorem, the more relaxed and practical sufficient stability conditions which are presented as a new set of linear matrix inequalities are put forward, which are guaranteed by rigorous mathematical derivation. The proposed control scheme is developed for fractional order non‐linear systems stabilisation in the presence of random disturbances. Typical instances including the fractional order three‐dimensional (3D) non‐linear system and the fractional order 4D non‐linear Lorenz hyperchaos are implemented. Simulation results indicate the designed fractional order T–S fuzzy control scheme works well compared with the existing method.

In the study, a novel fuzzy generalized predictive control (GPC) scheme is proposed for the stability control of nonlinear brushless DC motor (BLDCM). First, the fuzzy predictive model of BLDCM is presented via Takagi–Sugeno fuzzy model. Then, based on the controlled autoregressive moving average (CARMA) model transformed by Takagi–Sugeno fuzzy model of BLDCM, a new fuzzy GPC scheme for the nonlinear BLDCM is designed by combining fuzzy techniques and GPC theory, and the rigorous mathematical derivation is given. Finally, numerical simulations are implemented to verify the effectiveness and superiority of the proposed scheme. It also provides reference for other nonlinear even chaos control in actual project.