Fuzzy PID control system optimization and verification for oxygen-supplying management in live fish waterless transportation

Abstract

Live fish waterless transportation could be recognized as an essential supplement for water-based transportation due to its low oxygen consumption and less waste water pollution. The critical problem to maintaining the fish survival quality under such a unique transport strategy is accurately controlling the oxygen concentration in the container to be constantly at stable and high levels. This paper aims to propose an improved fuzzy PID control system based on the grey model with residual rectification by improved particle swarm optimized Gated Recurrent Unit (GM-IPSO-GRU) to realize advanced oxygen level control. In addition, it is also reinforced by adopting the improved grey wolf optimization (IGWO) for the majorization of control parameters (quantization factors, scale factors) with full consideration of fish size features. In this study, Turbot (Scophthalmus maximus) is taken as the test subject to verify the integrated control performance of the optimized fuzzy PID controller through simulated waterless live transportation under low-temperature conditions. The proposed control system is validated as more efficient than the traditional proportional integral derivative (PID) and fuzzy PID algorithms for handling its nonlinear, time-varying, and time lag problems well. In summary, the control group experiment shows that the newly-designed control system has the advantages of shorter stabilization time, minor overshoot, and strong anti-interference ability for oxygen level adjustment. Finally, applying this novel control technology can effectively improve oxygen adjustment efficiency and provide feasible quality control support for the deep optimization of the live fish circulation industry.