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针对自抗扰控制(AIDRC)多参数不易整定的问题,提出了一种基于二次函数的非线性PID(NLPID)控制律.该方法用二次函数模拟PID增益参数随误差变化的规律曲线,构造了一个非线性PID神经网络模型,利用最速下降法对各模拟曲线的系数进行在线调整,实现了基于神经网络的自适应自抗扰控制.仿真结果表明,与常规ADRC控制方法相比,文章方法减少了ADRC需调整的参数,并具有较好的控制效果.
Aiming at the problem of multi-parameter auto-disturbance rejection (AIDRC) difficult to tune, a quadratic function-based nonlinear PID (NLPID) control law is proposed.The quadratic function is used to simulate the curve of PID gain parameter with error variation, A nonlinear PID neural network model is constructed, and the steepest descent method is used to adjust the coefficients of each simulation curve online to realize adaptive ADRC based on neural network. The simulation results show that compared with the conventional ADRC control method, The method reduces the parameters to be adjusted by ADRC and has better control effect.