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Identification of nice nonlinear model and its internal control
Pages: 576-580
Year: Issue:  4
Journal: Electric Machines and Control

Keyword:  nonlinear modelsystem identificationneural networksinternal controlrobustness;
Abstract: A novel model identification and internal control method are proposed with the universal approxomation of neural networks to solve the hardness of establish of nice nonlinear model and its linearizing compensator. The system objective function is founded and optimized to capture the nicely nonlinear model and its linearizing compensator, utilizing traditional Back-Propagation algorithm, whose uniqueness is approved under some proper conditions. To improve the systerm robustness and reduce the uncertainty including model error and external disturbance,a nonlinear internal control system is designed on the compensated pseudo-linear system.The results show that the identified model and linearizing compensator are precise by optimizing the system objective function and the nicely nonlinear model can be linearized well. The internal controller designed on the compensated pseudo-linear system has good ability in robustness and the control system can track the reference signal accurately.
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