模糊神经网络PID和PSO-PID优化的荧光检测控制系统

针对核酸提纯、扩增、检测一体化设备的荧光检测系统多通道检测运动的快速性和稳定性，设计了三种基于PID控制器的控制策略，分别为模糊PID、模糊RBF神经网络PID和PSO-PID。经MATLAB仿真结果表明，模糊PID控制有较大的超调量和调节时间，震荡较大；模糊RBF神经网络PID控制的超调量十分小，调节时间较小，无震荡；PSO-PID控制有小幅度震荡和超调量，调节时间最短，可快速到达稳定状态。模糊RBF神经网络PID和PSO-PID控制步进电机的方式同模糊PID相比，没有了主观经验的影响，反应时间快、稳定性好，具有很好的自学习、自适应能力。

Fluorescence detection control system optimized by fuzzy neural network PID and PSO-PID

Aiming at the rapidity and stability of the multi-channel detection movement of the fluorescence detection system integrated with nucleic acid purification, amplification and detection, three control strategies based on PID controller are designed, which are fuzzy PID, fuzzy RBF neural network PID and pso-pid. Matlab simulation results show that the fuzzy PID control has a large overshoot and adjustment time, and the oscillation is large; the overshoot of Fuzzy RBF neural network PID control is very small, the adjustment time is small, and there is no vibration; pso-pid control has a small amplitude of vibration and overshoot, the adjustment time is the shortest, and it can quickly reach the stable state. Compared with fuzzy PID, fuzzy RBF neural network PID and pso-pid control of stepper motor have no subjective experience, fast response time, good stability, and good self-lea rning and self-adaptive ability.