摘要
设计了一个监督模糊神经网络 FNN 控制系统 ,它可以跟踪周期输入信号 .控制系统由永磁 PM 同步伺服电机以及监督 FNN位置控制系统组成 .监督 FNN控制系统由监督控制器和 FNN滑式控制器组成 .监督控制器可以在指定区域内稳定系统的状态 ,FNN滑式控制器由滑式控制和 FNN组成 .滑式控制有较好鲁棒性 ,FNN具有在线学习能力 .作者对监督 FNN控制系统进行了详细的理论分析和稳定性研究 .
We designed a supervisory fuzzy neural network (FNN) control system to tracked peridic reference input. The control system consists of a synchronous servomotor drive with a supervisory FNN position controller. The supercisory FNN controller comprises a supervisory controller, which a designed to stabilize the system states around a defined boundary region, and a FNN aliding mode controller, which combines the advantages of the sliding mode with robust characterristics and the FNN with online learning ability. The theoretical and stability analyses of the supervisory FNN controller are discussed in detail. Simulation result shows that the control system is robust with regard to plant parameter variations and external load disturance.
出处
《上海师范大学学报(自然科学版)》
2002年第1期35-41,共7页
Journal of Shanghai Normal University(Natural Sciences)