基于FNN的PID非线性系统位置控制

Position Control of Non-Linear System Based on PID of FNN

针对数学模型不确定的某操瞄控制系统的控制问题,特别是滞环因素给系统的控制精度造成的不利影响,提出了一种基于 Takagi-Sugeno 模型的模糊神经网络(FNN)和比例积分微分(PID)控制的位置控制器和一种基于实数编码的遗传算法优化模型,运用该优化模型优化了控制器参数。仿真结果表明,该控制器具有较好的鲁棒性,采用这种控制器,系统能够高精度、快速、平稳地调转到指定的位置。

A position controller based on FNN(Fuzzy Neural Network)and PID is proposed according to the control problem of manipulation and collimation control system whose model is uncertain.The time-delay of such kind of system backlash affects the precision of controlling.A new optimal model based on real-coded inheritance algorithms is used to optimize the parameters of the controller.Simula- tions show that the controller is robust,highly reliable,and the systems can quickly and steadily move to the given position with high precision.