轮询通信下基于隶属函数优化的T-S模糊模型预测控制OA

This paper investigates the membership-function-dependent model predictive control problem for Takagi-Sugeno(T-S)fuzzy systems under communication bandwidth constraints.Firstly,a round robin protocol is adopted to op-timize the data transmission mechanism between controllers and actuators,thereby reducing network load and improving data transmission reliability.Building upon this framework,a piecewise switched T-S fuzzy model is constructed by inte-grating token-dependent quadratic functions with premise variable space partitioning.Secondly,based on token-dependent piecewise Lyapunov function theory,a membership-function-token co-dependent terminal constraint set is designed and embedded into the online optimization problem to solve for feedback gain.Furthermore,continuous membership functions are approximated using staircase membership functions,while linear matrix inequality constraints incorporating shape in-formation of membership functions are introduced.Under the joint consideration of T-S fuzzy system nonlinearities and round robin protocol characteristics,sufficient conditions are derived to guarantee both asymptotic stability of the sys-tem and recursive feasibility of the algorithm.Finally,simulation experiments validate the effectiveness of the proposed membership-function-dependent T-S fuzzy predictive control strategy under round robin protocol.