改进的单神经元自适应PID控制算法在智能车速度控制系统中的研究与应用

Single neuron adaptive PID control algorithm is improved in the intelligent vehicle speed control system research and application in the

针对单神经元控制算法在电磁导航智能车速度控制中存在加权系数修正时间长、自适应能力差、系统不稳定的缺点,提出了将改进的单神经元自适应PID控制算法应用到智能车的调速系统中。改进的单神经元自适应PID控制算法优化了单神经元自适应PID控制算法中的加权系数学习修正部分,使得权系数在线修正不完全根据神经网络的学习原理,而是参考实际经验制定的,最终自适应地整定PID三个参数来实现智能车的速度控制。Matlab仿真测试表明,与单神经元自适应PID控制算法相比,改进的单神经元自适应PID控制算法在智能车速度控制中具有响应快,超调量小、自适应能力强的优点,大大提高了智能车控制系统的性能。

In view of the single neuron control algorithm in electromagnetic navigation of intelligent vehicle speed control in the weighted coefficient of correction time is long, the adaptive ability is poor, the shortcomings of system instability, put forward the improved single neuron adaptive PID control algorithm is applied to the speed control system of intelligent vehicles. Improved single neuron adaptive PID control algorithm to optimize the weighted coefficient of single neuron adaptive PID control algorithm study modified parts, makes the weight coefficient of correction is not completely online according to the principle of neural network learning, but the reference of practical experience, the final three adaptively adjusting PID parameters to realize the speed control of intelligent vehicle. Matlab simulation tests show that compared with single neuron adaptive PID control algorithm, the improved single neuron adaptive PID control algorithm in the intelligent vehicle speed control has quick response, less overshoot and adaptive ability, the advantages of greatly improving the performance of the control system of smart car.