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On a method of single neural PID feedback compensation control

机译：在单一神经PID反馈补偿控制的方法上

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摘要

A control structure based on PID controller, single neural PID controller and single neural PID identifier is proposed. The PID controller is used to maintain the stability in the early stage of the study process of the neural network as well as when the system is under disturbance. The single neural PID identifier performs online learning based on the control error. Then it transfers the parameter results to the single neural PID controller, successfully avoiding offline learning. Afterwards, the single neural PID controller performs further study based on the control parameters and the output of the PID controller, producing a feedback compensation control quantity in order to compensate the model error of the single neural PID identifiers. The simulation results shows that compared with traditional PID control method, the single neural PID feedback compensation control method obtains significant improvement in various control features and has relatively excellent robustness and static features.
机译：提出了一种基于PID控制器，单神经PID控制器和单个神经PID标识符的控制结构。 PID控制器用于在神经网络的研究过程的早期阶段保持稳定性，以及系统处于干扰时。单个神经PID标识符根据控制错误执行在线学习。然后它将参数结果传输到单个神经PID控制器，成功避免了离线学习。之后，单个神经PID控制器基于控制参数和PID控制器的输出执行进一步的研究，从而产生反馈补偿控制量，以补偿单个神经PID标识符的模型误差。仿真结果表明，与传统的PID控制方法相比，单个神经PID反馈补偿控制方法在各种控制特征中获得显着改善，并且具有相对优异的鲁棒性和静态特征。

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