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针对复杂非线性动态系统的模糊建模问题 ,基于 T- S模型提出一种自组织模糊辨识算法。改进后的算法简化了前提结构辨识的过程 ,并使前提参数辨识和结论参数辨识同时完成 ,极大地减少了参数辨识和结构辨识的计算量 ,能够保证在线辨识的要求。大量的仿真结果表明该算法具有收敛速度快、辨识精度高、稳定性好的特点 ,便于工程应用。
Aimed at the problem of fuzzy modeling of complex nonlinear dynamic systems, a self-organizing fuzzy identification algorithm based on T-S model is proposed. The improved algorithm simplifies the process of preconditioning structure identification and completes the precondition parameter identification and conclusion parameter identification at the same time, which greatly reduces the computational burden of parameter identification and structure identification and ensures the requirements of on-line identification. A large number of simulation results show that the algorithm has the characteristics of fast convergence, high identification accuracy and good stability, which is convenient for engineering application.