Abstract
In the biaxially stretched film (BOPP) thickness control system, the traditional PID and Active-Disturbance Rejection Controller (ADRC) can’t achieve the ideal control effect. The Smith prediction method is used in the essay to establish a discretization model for the BOPP thickness control system. Combining with BP self-learning algorithm, a fast self-learning improved ADRC control algorithm (FSADRC) is proposed. By means of the additional momentum term and the adaptive learning rate method, the nonlinear combination of the ADRC system is adjusted in real time, the optimal control parameters are found, and the parameters are self-tuned. As a consequence, the improved algorithm is applied to the biaxial tensile film thickness control model. The simulation results show that the method has the advantages of high response speed and strong self-adaptive ability, which can effectively improve the control performance of the BOPP thickness control system.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
