He Dingxin, Wang Haoping, Tian Yang, Ma Xingyu
Sino-French International Joint Laboratory of Automatic Control and Signal Processing (LaFCAS), School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China.
Sino-French International Joint Laboratory of Automatic Control and Signal Processing (LaFCAS), School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China.
ISA Trans. 2024 Apr;147:511-526. doi: 10.1016/j.isatra.2024.02.002. Epub 2024 Feb 5.
To address the trajectory tracking issue of upper-limb rehabilitation exoskeleton with uncertainties and external disturbances, this paper proposes a fractional-order ultra-local model-based model-free finite-time robust controller (FO-FTRC) using predefined performance sliding surface. Different from previous model-free control strategies, a novel multi-input multi-output (MIMO) fractional-order ultra-local model which is a virtual model is proposed to approximate the complex uncertain nonlinear exoskeleton dynamics in a short sliding time window. This allows the design of controller to be independent of any exoskeleton model information and reduces the difficulty of controller design. The developed robust model-free control method incorporates a fractional-order quasi-time delay estimator (FO-QTDE), unknown disturbance estimator (UDE) as well as prescribed performance sliding mode control (PPSMC). The FO-QTDE is utilized to estimate the unknown lumped uncertainties which employs short time delayed knowledge only about the control input. However, the low-pass filter is always added for FO-QTDE when disturbances change fast, which leads to unavoidable estimation error. Then, UDE is designed to further eliminate the estimation error of FO-QTDE to enhance control performance. The PPSMC is constructed to converge sliding surface to zero in a finite time. Besides, the sliding surface is always limited in performance boundaries. After that, the overall system stability and convergence analyses are demonstrated by using the Lyapunov theorem. Finally, with the comparison to other methods of α-variable adaptive model free control (α-AMFC), time-delay estimation-based continuous nonsingular fast terminal sliding mode controller (TDE-CNFTSMC), time delay estimation (TDE)-based model-free fractional-order nonsingular fast terminal sliding mode control (MFF-TSM) and fractional-order proportion-differential (PD), the co-simulation results on 7-degree-of-freedom (DOF) iReHave upper-limb exoskeleton virtual prototype and experiment results on 2-DOF upper-limb exoskeleton are obtained to illustrate the effectiveness and superiority of the proposed FO-FTRC method.
为解决存在不确定性和外部干扰的上肢康复外骨骼的轨迹跟踪问题,本文提出一种基于分数阶超局部模型的无模型有限时间鲁棒控制器(FO-FTRC),该控制器使用预定义性能滑模面。与以往的无模型控制策略不同,本文提出了一种新颖的多输入多输出(MIMO)分数阶超局部模型作为虚拟模型,用于在短滑模时间窗口内逼近复杂不确定的非线性外骨骼动力学。这使得控制器的设计独立于任何外骨骼模型信息,降低了控制器设计的难度。所开发的鲁棒无模型控制方法结合了分数阶准时间延迟估计器(FO-QTDE)、未知干扰估计器(UDE)以及规定性能滑模控制(PPSMC)。FO-QTDE用于估计未知的集总不确定性,该不确定性仅利用关于控制输入的短时延迟知识。然而,当干扰变化较快时,总是会为FO-QTDE添加低通滤波器,这会导致不可避免的估计误差。然后,设计UDE以进一步消除FO-QTDE的估计误差,从而提高控制性能。构建PPSMC以使滑模面在有限时间内收敛到零。此外,滑模面始终限制在性能边界内。之后,利用李雅普诺夫定理对整个系统的稳定性和收敛性进行了分析。最后,通过与α-变量自适应无模型控制(α-AMFC)、基于时延估计的连续非奇异快速终端滑模控制器(TDE-CNFTSMC)、基于时延估计(TDE)的无模型分数阶非奇异快速终端滑模控制(MFF-TSM)以及分数阶比例微分(PD)等其他方法进行比较,在7自由度(DOF)iReHave上肢外骨骼虚拟样机上获得了联合仿真结果,并在2自由度上肢外骨骼上获得了实验结果,以说明所提出的FO-FTRC方法的有效性和优越性。