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Intelligent Learning Control of Hydraulic Flow Regulating Pump with Neural Network Load Flow Identifier

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1 Author(s)
Xiao Li ; Fac. of Electromech. Eng., Guangdong Univ. of Technol., Guangzhou, China

To solve the problem of power loss of load flow detection in hydraulic flow regulating pump (HFRP), a new method to identify load flow by using neural network load flow identifier (NNLFI) is proposed. To improve the load flow regulating accuracy of HFRP with NNLFI, an intelligent learning control method is proposed. An intelligent learning controller is designed based on the combination of pid controller, fuzzy neural network controller (FNNC), learning mechanism and intelligent regulator. The proposed methods are applied to an electrohydraulic proportional controlled HFRP. The experimental results proved that the proposed methods can avoid the power loss of load flow detection and achieve the higher load flow regulating accuracy than traditional pid control. This provides an economical and available way for the load flow regulating of HFRP.

Published in:

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on  (Volume:2 )

Date of Conference:

7-8 Nov. 2009