Parameters optimization of human-simulated intelligent controller for Coriolis mass flowmeter based on quantum genetic algorithm
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TH814;TN98

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    Abstract:

    According to the amplitude deviation and its rate of change, the vibration process is divided into eight characteristic states, and the corresponding control modes are designed by using Heuristic and intuitionistic reasoning respectively. In order to solve the problem that the vibration characteristic state identification parameters and the control modal parameters are too many and not easy to set, the quantum genetic algorithm is used to optimize the controller parameters. The optimization principle, optimization flow chart and realization steps are given, and the experimental verification is carried out. The results show that the HSIC controller with optimized parameters can reduce the starting time by 0. 1 and 0. 6 s compared with PID controller, and its amplitude is stable, which proves the performance of the method.

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  • Online: November 20,2023
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