Research on low-quality waste heat recovery system based on fuzzy proportion integration differentiation control

Author:

Yanjun Xiao1,Yameng Zhang2,Nan Gao2,Kai Peng2,Wei Zhou2,Weiling Liu2

Affiliation:

1. Intelligent Detection and Control Laboratory, School of Mechanical Engineering, Hebei University of Technology, Tianjin, China

2. Hebei University of Technology, Tianjin, China

Abstract

In the current industrial production process, waste heat of low quality is seriously wasted. In order to effectively recover low-quality waste heat, the research group developed a small energy conversion device –Roots power machine. On this basis, the research group designed a low-quality waste heat efficient utilization system with the equipment as the core and successfully applied it to low-quality waste heat recovery. However, in the actual operation process, the system can not run stably due to the occasional fluctuation of the input gas source. In view of this, after the study of waste heat recovery system, the fluctuation of gas source can be controlled by different grades according to the degree of change. Fuzzy rules also divide variables into different grades to solve problems, and fuzzy control can convert continuous changes of airflow into discrete changes, which greatly reduces the complexity of the control system. Therefore, the research group proposed a control strategy based on fuzzy PID. The simulation results show that the adjustment time of fuzzy PID is within 7 s, and the adjustment effect is obviously better than that of traditional PID. The experimental results show that the speed deviation under the condition of air source fluctuation is within the speed fluctuation rate (±5%), and the speed deviation under the condition of sudden disturbance load is within the steady speed adjustment rate (±3.5%), both of which meet the requirements of indexes. Therefore, the fuzzy PID control strategy can further improve the stability of output speed, reduce airflow pulsation, and provide the possibility for grid-connected power generation.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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