水轮机调节系统的模糊神经网络控制*

将模糊神经网络与自适应控制相结合,设计出一种能对水轮机调节系统进行有效控制的基于模糊神经网络的自适应PID控制算法.对改进后的调节系统特性进行测试和仿真,并与常规的水轮机进行比较,验证了模糊神经网络控制方案的可行性.仿真结果表明,该算法实现了调节系统的在线自适应调整,更精确反映调节系统的动态变化过程.与其他方法相比,该算法具有更快的响应速度和更好的控制效果.

Fuzzy neural network control of hydraulic turbine governing system

Combing the fuzzy neural network (FNN) and the adaptive control, this paper designed an adaptive PID algorithm based on the fuzzy neural network, which could effectively control the hydraulic turbine governing system. Simulated the improved mathematic model. The simulation results proved the validity and superiority of the fuzzy neural network PID algorithm. The simulation results show that the algorithm not only retain the functions of fuzzy control, but also provide the ability to approach to the non linear system. Also implemented the dynamic process of the system could be reflected more precisely and the on line adaptive control. The algorithm is superior to other methods in response and control effect.