Abstract：A synchronous control scheme combining Elman neural network complementary sliding mode controller (CSMC) and cross-coupled controller (CCC) is proposed for synchronous feed problem of dual linear motors servo system. The dual linear motors servo system consists of two parallel permanent magnet linear synchronous motors (PMLSMs). Considering that the PMLSM is vulnerable to the influence of parameter variations, external disturbances and frictions and so on,the dynamic model with a lumped uncertainties was established. Then, the Elman neural network is used to replace the switching control rate of CSMC, Elman neural network CSMC is designed to estimate the value of the uncertainties and reduce the chattering phenomenon of the sliding mode control, so that it can guarantee high precision position tracking performance of PMLSM servo system. CCC is used to eliminate the coupling between the dual linear motors, thus the synchronous control of dual linear motors servo system can be realized. The experimental results show that the proposed method not only has better tracking performance, but also has stronger robust performance, the tracking error and synchronous error of the system can be obviously reduced.
金鸿雁, 赵希梅. 双直线电机伺服系统Elman神经网络互补滑模交叉耦合同步控制[J]. 电工技术学报, 2018, 33(21): 4971-4978.
Jin Hongyan, Zhao Ximei. Synchronous Control of Elman Neural Network Complementary Sliding Mode and Cross-Coupled Control for Dual Linear Motors Servo System. Transactions of China Electrotechnical Society, 2018, 33(21): 4971-4978.
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2018, Vol. 33 
