基于Sugeno型模糊神经网络和互补滑模控制器的双直线电机伺服系统同步控制

doi:10.19595/j.cnki.1000-6753.tces.180839

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Abstract A control method combined with Sugeno type fuzzy neural network (SFNN) synchronous compensator and complementary sliding mode controller (CSMC) is proposed for position synchronization control problems of dual linear motors servo system in a high precision direct drive gantry position stage. The permanent magnet linear synchronous motor (PMLSM) dynamic model with uncertainties such as parameter variations, external disturbances and friction forces was established, and CSMC is designed by the combination of generalized sliding surface and complementary sliding surface. CSMC can efficiently suppress the influence of uncertainties and weaken the chattering phenomenon in the traditional sliding mode controller (SMC), reduce the tracking errors of the system and achieve high precision position tracking. Meanwhile, SFNN synchronous controller is used to solve the dynamic parameter unmatched problems between two linear motors and the coupling phenomenon. SFNN can make error compensation for each axis, so that it can reduce the position synchronization error and guarantee synchronization control of the system. The experimental results show that the control method can significantly reduce the tracking error and synchronization error of the system, and further improve the accuracy of contour processing.

Key words： Dual linear motors servosystem Sugeno type fuzzy neural network(SFNN) complementary sliding mode controller(CSMC) uncertainties synchronization control

Received: 15 May 2018 Published: 17 July 2019

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TP273

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	Jin Hongyan
	Zhao Ximei

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Jin Hongyan,Zhao Ximei. Dual Linear Motors Servo System Synchronization Control Based on SugenoType Fuzzy Neural Network and Complementary Sliding Mode Controller[J]. Transactions of China Electrotechnical Society, 2019, 34(13): 2726-2733.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.180839 OR https://dgjsxb.ces-transaction.com/EN/Y2019/V34/I13/2726

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