基于模糊神经网络的水轮机调速器PID控制

PID Control of the Hydraulic Turbine Governor Based on Fuzzy Neural Network

针对水轮机调节系统参数时变、运行工况多变以及包含复杂非线性环节的特点,传统的PID控制策略难以满足系统各项运行指标。根据水轮机调速系统的数学模型,结合模糊控制的推理能力和神经网络的自学能力,提出基于模糊神经网络的水轮机调速器PID参数控制策略。仿真结果表明,相比于传统PID控制和模糊控制,所提控制策略的系统响应拥有更小的超调量和更短的调节时间。

Due to the characteristics of time-varying parameters,variable operating conditions and complex nonlinear links of the hydraulic turbine governor system,the traditional PID control strategy is not able to meet the operation indexes of the system.According to the mathematical model of hydraulic turbine governor system,and together with the reasoning ability of fuzzy control and the self-learning ability of neural network,this paper presents a new PID parameter control strategy of the hydraulic turbine governor based on fuzzy neural network.The simulation results show that,compared with the traditional PID control and fuzzy control,the system response of the proposed control strategy has smaller overshoot and shorter regulation time.