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Li Jingyuan
Yi Menglin
College of Mechanical
Engineering,
Huazhong University of Science
and Technology,
Wuhan 430074, China
Wang Yu
Duan Hao
Kunming Branch of 705
Research Institute,
Kunming 650118, China
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HIGH-ACCURACY
SYNCHRONIZATION CONTROL
WITH HYBRID
NEURAL NETWORKS
Abstract: A novel nonlinear control algorithm based on hybrid neural networks is presented to cope with the high-accuracy synchronization control problem for a dual-actuator electrohydraulic drive system which plays an important role for the development of elastomeric launchers. A new objective function for better synchronization performance is introduced and a learning algorithm to adjust the weights of the neural network, based on the gradient descent algorithm, is also derived. The hybrid neural network control algorithm guarantees high-accuracy synchronization performance of two motion cylinders and fast dynamic response as well as good stability of the control system. Proto-type test results on the dual-actuator electrohydraulic drive system verifys the effectiveness of the proposed approach.
Key words:
Neural network Synchronization control Electrohydraulic system |