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An ADRC Parameters Self-Tuning Control Strategy of Tension System Based on RBF Neural Network 被引量:1
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作者 Shanhui liu Haodi Ding +2 位作者 Ziyu Wang li’e ma Zheng li 《Journal of Renewable Materials》 SCIE EI 2023年第4期1991-2014,共24页
High precision control of substrate tension is the premise and guarantee for producing high-quality products in roll-to-roll precision coating machine.However,the complex relationships in tension system make the probl... High precision control of substrate tension is the premise and guarantee for producing high-quality products in roll-to-roll precision coating machine.However,the complex relationships in tension system make the problems of decoupling control difficult to be solved,which has limited the improvement of tension control accuracy for the coating machine.Therefore,an ADRC parameters self-tuning decoupling strategy based on RBF neural network is proposed to improve the control accuracy of tension system in this paper.Firstly,a global coupling nonlinear model of the tension system is established according to the composition of the coating machine,and the global coupling model is linearized based on the first-order Taylor formula.Secondly,according to the linear model of the tension system,a parameters self-tuning decoupling algorithm of the tension system is proposed by integrating feedforward control,ADRC and RBF.Finally,the simulation results show that the proposed tension control strategy has good decoupling control performance and effectively improves the tension control accuracy for the coating machine. 展开更多
关键词 Coating machine tension system decoupling control ADRC RBF
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