Fuzzy Control of Cold Storage Refrigeration System with Dynamic Coupling Compensation

Abstract

Cold storage refrigeration systems possess the characteristics of multiple input and output and strong coupling, which brings challenges to the optimize control. To reduce the adverse effects of the coupling and improve the overall control performance of cold storage refrigeration systems, a control strategy with dynamic coupling compensation was studied. First, dynamic model of a cold storage refrigeration system was established based on the requirements of the control system. At the same time, the coupling between the components was studied. Second, to reduce the adverse effects of the coupling, a fuzzy controller with dynamic coupling compensation was designed. As for the fuzzy controller, a self-tuning fuzzy controller was served as the primary controller, and an adaptive neural network was adopted to compensate the dynamic coupling. Finally, the proposed control strategy was employed to the cold storage refrigeration system, and simulations were carried out in the condition of start-up, variable load, and variable degree of superheat, respectively. The simulation results verify the effectiveness of the fuzzy control method with dynamic coupling compensation.

Environmental Health Oriented Optimal Temperature Control for Refrigeration Systems Based on a Fruit Fly Intelligent Algorithm

“…Several methods have been used for the control of refrigeration systems. In Ma’s and Bayram’s studies [7,8], fuzzy logic control was applied to control the temperature of a refrigeration system, while in Pedersen’s study [9], a neural network is combined with a gain scheduling-based PI controller to control the overheating of a refrigeration system. In addition, in Yin’s and Schalbart’s studies [10,11], MPC controllers are utilized to control refrigeration systems, and a L-Band SBQP-Based MPC control scheme has also been applied to control two different devices in a supermarket refrigeration system [12].…”