This article addresses the reference tracking issue of multi-degree-of-freedom robotic exoskeletons under exogenous perturbations. First, by considering the concept of iteration-dependent full-format dynamic linearization, the exoskeleton robot’s dynamics is reformulated as a linear data model in an iterative manner. Then, based upon an iterative sliding variable, a novel data-based model-free adaptive iterative learning integral terminal sliding mode control is designed. The superiority of the proposed study is that the reference tracking problem is just solved by using the measured input/output information of exoskeletons. In addition, its finite-iteration convergence is also affirmed by mathematical analysis. The simulation investigation together with the compared results also clarifies the efficiency of the developed learning-based control algorithm.

本文解决了外源扰动下多自由度机器人外骨骼的参考跟踪问题。首先，通过考虑依赖迭代的全格式动态线性化的概念，外骨骼机器人的动力学以迭代方式重新表述为线性数据模型。然后，基于迭代滑动变量，设计了一种新颖的基于数据的无模型自适应迭代学习积分终端滑模控制。所提出的研究的优势在于，参考跟踪问题只是通过使用外骨骼的测量输入/输出信息来解决的。此外，其有限迭代收敛性也得到了数学分析的肯定。