Optimization for PID controller of cryogenic ground support equipment based on cooperative random learning particle swarm optimization

Cryogenic ground support equipment (CGSE) is an important part of a famous particle physics experiment — AMS-02. In this paper a design method which optimizes PID parameters of CGSE control system via the particle swarm optimization (PSO) algorithm is presented. Firstly, an improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. Secondly, the way of finding PID coefficient will be studied by using this algorithm. Finally, the experimental results and practical works demonstrate that the CRPSO-PID controller achieves a good performance.     

Control system design and test for cryogenic ground support equipment

The cryogenic ground support equipment (CGSE) is an important part of Alpha Magnetic Spectrometer-02 (AMS-02) experiment which is a particle physics experiment. CGSE is used to cool down the superconducting magnet of AMS-02 to its operating temperature of 1.8K and to fill the magnet helium tank with superfluid helium. This paper introduces the control system of CGSE and presents the performance of the system.