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Volume 4, Issue 4
A Model Reference Adaptive Control Based on Fuzzy Neural Network for Some Weapon Ac Servo System

Huawei CHAI, Longxing YANG

J. Info. Comput. Sci. , 4 (2009), pp. 299-306.

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  • Abstract
Abstract.This paper presents a novel model reference adaptive control algorithm based on fuzzy neural network. This widely used method is utilized to adjust the parameters on line. The fuzzy neural network sliding mode controller,which integrates the fuzzy neural network with sliding mode controller, is put forward to control some weapon servo system with model uncertainties and parameters variation. Because this proposed algorithm combines excellences of FNN and sliding mode control, it has the ability to eliminate the drawbacks of traditional SMC, i.e. the chattering in the control signal and needing knowledge of bounds of uncertainties. Simulation results verify this proposed algorithm can reduce the plant’s sensitivity to parameter variation and disturbance.
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@Article{JICS-4-299, author = {Huawei CHAI, Longxing YANG}, title = {A Model Reference Adaptive Control Based on Fuzzy Neural Network for Some Weapon Ac Servo System}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {4}, number = {4}, pages = {299--306}, abstract = {Abstract.This paper presents a novel model reference adaptive control algorithm based on fuzzy neural network. This widely used method is utilized to adjust the parameters on line. The fuzzy neural network sliding mode controller,which integrates the fuzzy neural network with sliding mode controller, is put forward to control some weapon servo system with model uncertainties and parameters variation. Because this proposed algorithm combines excellences of FNN and sliding mode control, it has the ability to eliminate the drawbacks of traditional SMC, i.e. the chattering in the control signal and needing knowledge of bounds of uncertainties. Simulation results verify this proposed algorithm can reduce the plant’s sensitivity to parameter variation and disturbance. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22739.html} }
TY - JOUR T1 - A Model Reference Adaptive Control Based on Fuzzy Neural Network for Some Weapon Ac Servo System AU - Huawei CHAI, Longxing YANG JO - Journal of Information and Computing Science VL - 4 SP - 299 EP - 306 PY - 2024 DA - 2024/01 SN - 4 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22739.html KW - ac servo system KW - position control KW - fuzzy neural network AB - Abstract.This paper presents a novel model reference adaptive control algorithm based on fuzzy neural network. This widely used method is utilized to adjust the parameters on line. The fuzzy neural network sliding mode controller,which integrates the fuzzy neural network with sliding mode controller, is put forward to control some weapon servo system with model uncertainties and parameters variation. Because this proposed algorithm combines excellences of FNN and sliding mode control, it has the ability to eliminate the drawbacks of traditional SMC, i.e. the chattering in the control signal and needing knowledge of bounds of uncertainties. Simulation results verify this proposed algorithm can reduce the plant’s sensitivity to parameter variation and disturbance.
Huawei CHAI, Longxing YANG. (2024). A Model Reference Adaptive Control Based on Fuzzy Neural Network for Some Weapon Ac Servo System. Journal of Information and Computing Science. 4 (4). 299-306. doi:
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