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The elevator is a kind of complex system with time-varying and strong-coupling characteristics. For elevator systems, with use of traditional PID algorithm, as there are disadvantages of difficult optimal parameters selection, weak steady-state behavior, etc., it is difficult to achieve satisfactory control effect. Therefore, this article discusses the theory of using RBF neural network to identify...
Depth parking control is important for the HTPE (HydroThermal Plume Explorer). It aims to have a more accurate parking depth and a less oscillation at the target depth. The plant approaching and motion forecasting model based on RBF neural network is built to self-adjust and approach online motion law of HTPE in ideal circumstance of the sea, and simulate output of given control quantity after an...
An adaptive neural network control of a novel type of translational meshing motor with model uncertainties is considered. Owing to its nonlinear characteristic, a model reference control system which consists of two neural networks is used. The torque model is identified based on BP neural network, and then a RBF neural network works as the controller. The model reference control system is trained...
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