基于RBF神经网络电液恒功率调速自整定PID控制

Self-tuning PID Control of Electric Hydraulic Constant Power Speed Regulation Based on RBF Neural Network

采煤机电液调速系统对保证煤矿生产具有重要的作用。在分析恒功率自动调速的电液控制系统原理的基础上,建立了基于RBF神经网络自整定的PID控制的数学模型。通过在MATLAB/GUI仿真平台上计算得到系统的实际输出和模型输出的误差不超过5%,设计的RBF神经网络的电液恒功率调速自整定PID控制系统具有更高的跟踪精度和响应特性,完全可以实现系统的高精度与快速调速控制。

The electrical hydraulic speed control system of coal mining mechanical plays an important role to ensure the coal mine production. Based on the analysis about the principle of the electro-hydraulic control system of constant power automatic speed control, the mathematical model of the self-tuning PID control was built by using the RBF neural network self-tuning PID control strategy. By MATLAB/GUI simulation platform, the output error between the real output and the model output was less than 5%. It is shown the designed electric hydraulic constant power speed regulation self-tuning PID control system has higher tracking precision and response characteristics, by which high precision and fast speed regulation control can be achieved.