This article develops an asymptotic tracking control strategy for uncertain nonlinear systems subject to additive disturbances and parametric uncertainties. To fulfill this work, an adaptive-gain disturbance observer (AGDO) is first designed to estimate additive disturbances and compensate them in a feedforward way, which eliminates the impact of additive disturbances on tracking performance. Meanwhile, an updated observer gain law driven by observer estimation errors is adopted in AGDO, which reduces the conservatism of observer gain selection and is beneficial to practical implementation. Also, the parametric uncertainties existing in systems are addressed via an integrated parametric adaptive law, which further decreases the learning burden of AGDO. Based on the parametric adaption technique and the proposed AGDO approach, a composite controller is employed. The stability analysis uncovers the system asymptotic tracking performance can be attained even when facing time-variant additive disturbances and parametric uncertainties. In the end, comparative experimental results of an actual mechatronic system driven by a dc motor uncover the validity of the developed approach.

本文为受加性扰动和参数不确定性影响的不确定非线性系统开发了一种渐近跟踪控制策略。为了完成这项工作，首先设计了自适应增益扰动观测器（AGDO）来估计加性扰动并以前馈方式对其进行补偿，从而消除了加性扰动对跟踪性能的影响。同时，AGDO采用了由观测器估计误差驱动的更新观测器增益定律，降低了观测器增益选择的保守性，有利于实际实现。此外，系统中存在的参数不确定性通过集成的参数自适应法则得到解决，这进一步降低了 AGDO 的学习负担。基于参数自适应技术和提出的 AGDO 方法，采用复合控制器。稳定性分析表明，即使面临时变加性扰动和参数不确定性，系统也可以获得渐近跟踪性能。最后，由直流电机驱动的实际机电系统的比较实验结果揭示了所开发方法的有效性。