介绍了人体表面的低温现象与低温治疗的控制平台。该控制平台以MSP430微处理器为控制核心, 以上位机及TFT触摸液晶屏作为操作显示界面, 以基于蚁群算法的变参数预测PID作为核心算法, 该算法通过将神经网络作为预测模型, 利用蚁群算法的全局寻优能力在线优化PID的控制参数,实时监控人体的温度。实验结果表明, 系统经该算法处理后, 单位阶跃响应的超调量和调控时间大幅减少, 动态和稳定性得到了大幅改善, 能准确而迅速地将人体表面温度值稳定在要求范围之内。

The hypothermia phenomenons on body surface and hypothermia therapy control platform are introduced. MSP430 microprocessor is taken as a key control part, upper computer and thin film transistor (TFT) LCD touch screen as operation display interface and variable parameter prediction proportion integral derivative (PID) based on ant colony algorithm as key algorithm. Neural network is taken as prediction models and the control parameter of PID is optimized on line using the global optimization ability of ant colony algorithm to monitor the temperature of human body in real time. Experimental results show that unit step response overshoot and adjustment time are drastically reduced, dynamics and stability has been significantly improved and the surface temperature of human body can be stabilized accurately and rapidly in the range of requirements processed by the algorithm.