基于扰动补偿的无微分模型参考自适应控制系统设计

针对一类含有参数不确定性和未知非线性扰动的系统,本文提出一种基于扰动补偿的无微分模型参考自适应控制方法,实现系统输出对参考模型输出信号的高精度跟踪.首先,利用被控对象模型信息设计扰动估计器,对系统非线性扰动进行在线估计;其次,基于非线性扰动估计值设计参考模型和无微分参数更新律,构建无微分模型参考自适应控制器,建立基于扰动补偿和状态反馈的自适应控制律,以消除参数不确定性和非线性扰动对系统输出的影响,保证系统输出对参考模型输出的准确跟踪;然后,给出闭环系统误差信号收敛条件和控制器参数整定方法;最后,通过数值仿真验证所提方法的有效性和优越性.

Design of derivative-free model-reference adaptive control for a class of uncertain systems based on disturbance compensation

This paper presents a derivative-free model-reference adaptive control (DF-MRAC) method for a class of systems with parameter uncertainties and nonlinear disturbances based on the active disturbance estimation and compensation approach so as to achieve the high-precision tracking for reference model output signal. First, exploiting the available model information of the controlled plant, a disturbance estimator is esigned to estimate the unknown nonlinear disturbances. Next, a reference model based on the estimate of nonlinear disturbances and a derivative-free parameter update law are designed to estimate the parameter uncertainties. The estimate of uncertainties is incorporated into a DF-MRAC controller to yield an adaptive control law based on the disturbance compensation and state feedback that effectively compensate for the nonlinear disturbances and parameter uncertainties. Then, the convergence conditions for the error signals of the closed-loop system are investigated and a regulation method for the controller parameters is developed. Finally, simulation results demonstrate the effectiveness and superiority of the proposed method.