基于T-S模糊模型的自适应重构控制

针对建模误差,外界干扰及操作故障等因素对重构控制的影响,提出了一种基于T-S模糊模型的自适应重构控制方案。整个方案基于模糊T-S模型,在与神经网络的学习能力相结合后,使模糊控制器能自动调整它的隶属度函数,为模糊控制器增加了相当的灵活性,可重构的控制律又使系统在故障情况下的输出精确跟踪期望参考模型的输出,可以有效地补偿故障引起的非线性因素的影响。仿真结果表明了所提出的方法的有效性。

Adaptive Reconfigurable Control Based on T-S Fuzzy Model

A adaptive reconfigurable control method is presented based on T-S fuzzy model which contraposes the effect of the reconfigurable control caused by the modeling error, disturbance or system failure and maintains the handling qualities of the system. Based on T-S fuzzy model, the controller can turn membership function automatically through the overall control scheme being constructed by the learning ability of neural network, and the controller can be improved the flexibility through the same way. The law of reconfigurable control can make the outputs of impaired system tracking those of reference model accurately. and it can be used to compensate non-linear dynamics caused by failure. Simulation shows that the reconfigurable method receives a good effect.