一种基于T-S云模型的非线性系统控制

将云模型与T-S模糊系统结合,利用隶属云代替模糊系统的前件,提出一种T-S云模型.T-S云模型综合考虑模型的精确性和可解释性,不但可以利用专家的知识和经验建立系统模型,而且还可以通过输入/输出数据设计云模型系统.详细分析T-S云模型的系统结构.基于云模型和模糊系统对模糊概念表述的一致性,在不考虑超熵的情况下,使用梯度下降法辨识T-S云模型前件参数.利用递推最小二乘法辨识T-S云模型后件参数.设计了基于T-S云模型的控制器,实现了将卡车后倒至指定的卸车位置,体现了T-S云模型的不确定处理能力.仿真研究验证了算法的有效性.

T - S cloud model for nonlinear systems control

The integration of cloud model and T - S fuzzy system was considered. The antecedents of the fuzzy system were replaced by the membership clouds. And a T - S cloud model was proposed. The T -S cloud model balances the trade-off between accuracy and interpretability. The system model can be designed not only through the expert knowledge and experience but also the input/output data. The structure of cloud model system was analyzed. The concept of fuzzy is consistent in cloud model and fuzzy systems. Therefore without considering the hyper-entropy,an iterative gradient-descent algorithm was used to update the antecedent parameters of the T - S cloud model. Then the consequent parameters were calculated by recursive least square method. A controller based on the T - S cloud model was developed to back up the truck. Simulation results show the effectiveness of the proposed method.