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Data-Based Online Optimal Temperature Tracking Control in Continuous Microwave Heating System by Adaptive Dynamic Programming

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Abstract

Control of continuous microwave heating system (CMHS) is truly a complex problem with time variance, uncertainty and nonlinearity, which becomes prohibitive to use a conventional model-based approach. To overcome this, a novel data-based optimal temperature tracking control is designed for CMHS in this paper. In order to obtain the complex dynamics of CMHS, a neural network model is first constructed driven by process data. After transforming the original temperature tracking problem into an error regulation problem, adaptive dynamic programming is introduced to deal with the regulation problem as well as to decrease operation cost. The design and operation of this controller depend mainly on the online data, and minor prior knowledge is required. Simulation results show that the proposed method can effectively control the CMHS in terms of temperature tracking and energy utilization.

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Funding

This work was supported by the National Natural Science Foundation of China under Grant 61771077, the Key Research Program of Chongqing Science & Technology Commission under Grant CSTC2017jcyjBX0025 and the UK Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/P004636/1.

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Authors and Affiliations

  1. Key Laboratory of Complex System Safety and Control (Ministry of Education), Chongqing University, Chongqing, 400044, China

    Tong Liu, Shan Liang, Qingyu Xiong & Kai Wang

  2. School of Automation, Chongqing University, Chongqing, 400044, China

    Tong Liu, Shan Liang & Kai Wang

  3. School of Big Data & Software Engineering, Chongqing University, Chongqing, 401331, China

    Qingyu Xiong

Authors
  1. Tong Liu
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  2. Shan Liang
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  3. Qingyu Xiong
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  4. Kai Wang
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Correspondence to Shan Liang.

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Liu, T., Liang, S., Xiong, Q. et al. Data-Based Online Optimal Temperature Tracking Control in Continuous Microwave Heating System by Adaptive Dynamic Programming. Neural Process Lett 51, 167–191 (2020). https://doi.org/10.1007/s11063-019-10081-1

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