Research on load simulator control strategy based on BP neural network and PID method

Author:

Zhou Yong,Zhang Yubo,Yang Tianhao

Abstract

In the research of load simulator control method, PID control is the most widely used control strategy, but PID controller’s three parameters is difficult to set. This paper proposes a BP neural network feedforward PID controller system which uses BP neural network for setting these parameters, and in order to make the network learning speed up the convergence speed and not fall into local minimum, the adaptive vector method is adopted to improve the algorithm. The simulation and experimental results show that this method is good at avoiding the primeval shock and the sine tracking performance of the system has also been improved.

Publisher

EDP Sciences

Subject

General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Cascade BP Neural Network Tuned PID Controller for a High-Voltage Cable-Stripping Robot;Micromachines;2023-03-20

2. PID Controller based on BP Neural Network for Speed Control of Electric Vehicle;2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC);2022-11-10

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