袁中凡, 廖俊必, 赵世平. 利用神经网络进行综合机构的建模和控制[J]. 工程科学学报, 2003, 25(3): 277-279. DOI: 10.13374/j.issn1001-053x.2003.03.049
引用本文: 袁中凡, 廖俊必, 赵世平. 利用神经网络进行综合机构的建模和控制[J]. 工程科学学报, 2003, 25(3): 277-279. DOI: 10.13374/j.issn1001-053x.2003.03.049
YUAN Zhongfan, LIAO Junbi, ZHAO Shiping. Modelling and Control of Hybrid Mechanisms Using Neural Network[J]. Chinese Journal of Engineering, 2003, 25(3): 277-279. DOI: 10.13374/j.issn1001-053x.2003.03.049
Citation: YUAN Zhongfan, LIAO Junbi, ZHAO Shiping. Modelling and Control of Hybrid Mechanisms Using Neural Network[J]. Chinese Journal of Engineering, 2003, 25(3): 277-279. DOI: 10.13374/j.issn1001-053x.2003.03.049

利用神经网络进行综合机构的建模和控制

Modelling and Control of Hybrid Mechanisms Using Neural Network

  • 摘要: 介绍了逆模型超前控制器,神经网络反馈单元及由5层神经网络组成的集成控制系统.集成控制系统包括一个由神经网络组成的系统模型和具有自调整功能的控制单元.该方法被用于优化设计的综合机构控制仿真,结果证明了它的先进性和可行性.

     

    Abstract: To realize the optimized hybrid machine benefits in practice, a control system is designed. These comprise an inverse model feed-forward controller with a neural network feedback element and a integrate neural network in which the controller and plant model are combined to form a five-layer neural network. The neural network feedback element constructs a self-tuning loop. The results indicate their potential for practical use and their feasibility.

     

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