科氏流量计仿人智能控制器参数的量子遗传优化

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

设计的科氏流量计仿人智能振幅控制器根据振幅偏差及其变化率将振动过程划分为8种特征状态,利用启发式搜索和直觉推理,分别设计相应的控制模态,从而实现振动控制;针对控制器中振动特征状态识别参数与控制模态参数较多且不易设置的问题,采用量子遗传优化算法实现控制器参数优化,给出了优化原理、优化流程和实现步骤,并进行实验验证。结果表明,参数优化后仿人智能控制器起振时间较优化前减少约0.1 s、较PID控制减少约0.6 s,且振幅稳定,验证了方法性能。

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.