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针对单神经元自适应PID控制算法在电磁导航智能车角度偏差处理中存在输出误差和控制增量大的缺点,提出了基于二次型性能指标学习算法的单神经元自适应PID控制算法。在加权系数的调整中引入二次型性能指标,使输出误差和控制增量的加权平方和为最小来调整加权系数,从而间接实现对输出误差和控制增量加权的约束控制。Matlab仿真测试表明,与单神经元自适应PID控制算法相比,二次型性能指标学习算法在智能车角度控制中具有响应快,超调量小、鲁棒性和适应性强的优点,大大提高了智能车舵机控制系统的性能。
A single neuron adaptive PID control algorithm has the shortcomings of output error and control increment in the angle deviation of electromagnetic navigation smart car. A single neuron adaptive PID control algorithm based on quadratic performance index learning algorithm is proposed. The quadratic performance index is introduced into the adjustment of the weighting coefficient so that the weighted sum of the output error and the control increment is minimized to adjust the weighting coefficient so as to realize the constraint control of the output error and the control increment indirectly. Matlab simulation results show that compared with the single neuron adaptive PID control algorithm, quadratic performance index learning algorithm has the advantages of fast response, small overshoot, robustness and adaptability in intelligent vehicle angle control. Improve the performance of smart car steering gear control system.