Abstract
In order to obtain good control performance of ultrasonic motors in real applications, a study on the learning in intelligent control using neural networks (NN) based on differential evolution (DE) is reported in this chapter. To overcome the problems of characteristic variation and nonlinearity, an intelligent PID controller combined with DE type NN is studied. In the proposed method, an NN controller is designed for estimating the variation of PID gains, adjusting the control performance in PID controller to minimize the error. The learning of NN is implemented by DE in the update of the NN’s weights. By employing the proposed method, the characteristic changes and nonlinearity of USM can be compensated effectively. The effectiveness of the method is confirmed by experimental results.
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Mu, S., Shibata, S., Lu, H., Yamamoto, T., Nakashima, S., Tanaka, K. (2022). Study on the Learning in Intelligent Control Using Neural Networks Based on Back-Propagation and Differential Evolution. In: Mu, S., Yujie, L., Lu, H. (eds) 4th EAI International Conference on Robotic Sensor Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-70451-3_2
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