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Abstract: A new control structure for load simulator to improve its
performance is presented, in which there are three RBF neural networks
applied, one is taken as NN PID controller, the second is taken as
compensator for adjusting anti-disturbance coefficient dynamically, the
third one is use for identifying the plant (NNI). The neural network PID
controller is designed by requirement for steady, which overcome the
shortcoming of the only neural network controller. A RBF neural network
is used to identify the plant, in which the Jacobian matrix is got to
use for adjusting disturbance-reduced parameter in the compensating
neural network. The simulation and experiment are carried out, which
show a good result. This method is of validity and robustness.
Key words: Electric-hydraulic load simulator Neural network
controller Intelligent PID Compensation of extraneous force
CLC No: TH137
国家自然科学基金资助项目(50075006).
Received 20020313, received in revised form 20020628
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