排序方式: 共有4条查询结果,搜索用时 15 毫秒
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Zaki Ahmad M. El-Nagar Ahmad M. El-Bardini Mohammad Soliman F. A. S. 《Neural computing & applications》2021,33(5):1515-1531
Neural Computing and Applications - For the current paper, the technique of feed-forward neural network deep learning controller (FFNNDLC) for the nonlinear systems is proposed. The FFNNDLC... 相似文献
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Elkenawy Ahmed El-Nagar Ahmad M. El-Bardini Mohammad El-Rabaie Nabila M. 《Neural computing & applications》2021,33(15):9221-9240
Neural Computing and Applications - This study introduces a neural network (NN) adaptive tracking controller-based reinforcement learning (RL) scheme for unknown nonlinear systems. First, an... 相似文献
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Hossam Mohammad Khalil Mohammad El-Bardini 《Expert systems with applications》2011,38(11):14249-14256
The performance of a model-based control system depends strongly on the accuracy of the process model used. LS-SVM is a powerful method for modeling nonlinear systems. The main objective of this paper is to implement a conventional controller based on LS-SVM model for hydraulic motor. An off-line model is first identified based on LS-SVM, then via simulation tests the parameters of the discrete PI-Controller and its velocity-form are obtained then the controller parameters are applied experimentally for the hydraulic motor as a speed controller. The system performance has been evaluated; results show good performance over a wide range of operating conditions and load disturbances. 相似文献
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In this paper, the interval type-2 fuzzy proportional–integral–derivative controller (IT2F-PID) is proposed for controlling an inverted pendulum on a cart system with an uncertain model. The proposed controller is designed using a new method of type-reduction that we have proposed, which is called the simplified type-reduction method. The proposed IT2F-PID controller is able to handle the effect of structure uncertainties due to the structure of the interval type-2 fuzzy logic system (IT2-FLS). The results of the proposed IT2F-PID controller using a new method of type-reduction are compared with the other proposed IT2F-PID controller using the uncertainty bound method and the type-1 fuzzy PID controller (T1F-PID). The simulation and practical results show that the performance of the proposed controller is significantly improved compared with the T1F-PID controller. 相似文献
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