MatchaDB

2021Journal articleFree to read

Research on Intelligent Blending Method of Matcha Based on Improved PID Control Algorithm

Kai Chen, Jie Yu, Miao Hao, Chengmei Zhang, Bing Yang, Hong‐Zhou Tan, Yajie Wang

Journal of Physics Conference Series

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Abstract

Abstract Most of the existing Matcha blending is done manually, which is inefficient and leads to uneven tea products. To solve this problem, this paper proposes an intelligent blending method based on improved PID control algorithm. In this paper, considering the various factors that affect the quality of tea, without affecting the quality of the product, taking the lowest cost of the enterprise as the constraint goal, the basic combination model is constructed by using PID control algorithm. Since the selection of PID parameters will affect the output of the model, this paper introduces particle swarm optimization algorithm to optimize the PID controller parameters globally, so that the PID controller can achieve the ideal control index, and finally determine the optimal combination of Matcha. The experimental results show that the method proposed in this paper can effectively realize the intelligent blending of Matcha, and maximize the cost of tea factory, effectively improve the income of Matcha products, which is conducive to the further development of tea companies.

Abstract text comes from PubMed, OpenAlex or Europe PMC and belongs to the authors and publisher.

Study type

Other / not stated

Assigned automatically from the title, abstract and subject terms.

Topics

Processing, milling and quality

Matcha is a main subject here (named in the title).

Keywords and subject terms

PID controlparticle swarm optimizationPID controller tuningtea qualitycost minimization

Cite this study

Kai Chen, Jie Yu, Miao Hao, Chengmei Zhang, Bing Yang, Hong‐Zhou Tan, Yajie Wang. (2021). Research on Intelligent Blending Method of Matcha Based on Improved PID Control Algorithm. Journal of Physics Conference Series. https://doi.org/10.1088/1742-6596/1848/1/012014

DOI: 10.1088/1742-6596/1848/1/012014 · Cited by 5 (OpenAlex)

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