Noise-rejection zeroing dynamics for control of industrial agitator tank


Agitator tanks are widely used in industrial fields. Improvement in their efficiency is critical to achieving high productivity. That is to say, an agitator tank system should have a short response time to produce a desired reagent with an accurate solution concentration and a moderate liquid level. Therefore, a noise-rejection zeroing dynamics (NRZD) model for the control of the agitator tank based on a neural-dynamics method with anti-noise performance is proposed in this paper. The solution concentration and the liquid level of the agitator tank synthesized by the NRZD model are able to converge to the desired trajectories polluted with different noises. Then, theoretical analyses on the convergence and anti-noise performance of the agitator tank system equipped with the NRZD model are presented. Furthermore, to verify the superiority of the agitator tank system equipped with the NRZD model, we perform tracking trajectories simulations on solution concentration and the liquid level of the agitator tank with different noises. Moreover, the simulation results verify that the NRZD model is more effective than the existing models in the reagent preparation process.

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This study was funded by the National Key Research and Development Program of China under Grant 2017YFE0118900, by the research project of Huawei Mindspore Academic Award Fund of Chinese Association of Artificial Intelligence CAAIXSJLJJ-2020-009A, by the Team Project of Natural Science Foundation of Qinghai Province, China (No. 2020-ZJ-903), by the Key Laboratory of IoT of Qinghai (No. 2020-ZJ-Y16), by the Natural Science Foundation of Gansu Province, China, under Grant 20JR10RA639, by the Natural Science Foundation of Chongqing (China) under Grant cstc2020jcyj-zdxmX0028, by the Research and Development Foundation of Nanchong (China) under Grant 20YFZJ0018, by CAS “Light of West China” Program, and by the Project Supported by Chongqing Key Laboratory of Mobile Communications Technology under Grant cqupt-mct-202004.

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Correspondence to Long Jin.

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Liu, M., Li, J., Liufu, Y. et al. Noise-rejection zeroing dynamics for control of industrial agitator tank. Nonlinear Dyn (2021).

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  • Agitator tank system
  • Production efficiency
  • Noise rejection zeroing dynamics (NRZD)
  • Computer simulations