This article presents a robust finite-time command-filtered backstepping control strategy for flexible-joint robotic systems with only position measurements. To the best of our knowledge, this method is proposed for the first time and applied to the flexible-joint robot (FJR) system subject to matched/mismatched disturbances. Herein, two finite-time disturbance observers (FTDOs) are adopted to reconstruct unmeasurable system states and total matched and mismatched disturbances. By combining a finite-time command-filtered backstepping controller with two FTDOs, a novel robust command-filtered backstepping controller is presented. Meanwhile, the practically finite-time stability analysis of the closed-loop system is rigorously presented by the Lyapunov function. Finally, numerical simulations and experimental studies are carried out for the FJR, whose results show the superiority of the proposed scheme in comparison with the existing approaches, such as the FTCFBC, the ADRC, and the CSMC.

This article proposes a robust command-filtered control method with prescribed performance for flexible-joint robots (FJRs) wherein matched and mismatched disturbances are compensated by designing generalized proportional integral disturbance observers (GPIOs). The contributions are threefold. Firstly, a prescribed performance function (PPF), compared with that of the previous schemes, frees the assumption that the initial value of tracking errors within a predetermined region and thus is global, which brings dynamic response and steady-state precision benefits. Secondly, unlike most existing backstepping controllers that handle only internal uncertainties, the method presented here also considers time-varying external disturbances which may affect the tracking performance of the FJRs. Thirdly, a second-order command filter and a filter error compensation method are designed to avoid the ”complexity explosion” problem encountered in the traditional backstepping scheme. Analysis with the Lyapunov function proves the asymptotical stability of the closed-loop system. Simulation and experiments are performed to validate the feasibility and fine performance of the recommended control strategy.

This article investigates the torque tracking problem of series elastic actuators (SEAs) that are affected by nonlinear uncertainty and actuator saturation. An unknown system dynamics estimator (USDE), which has only one parameter to be turned, is designed to provide an estimation of the nonlinear uncertainty. Then, based on the estimation, a composite proportional-derivative with sliding-mode control (PD-SMC) method is proposed to solve the problem. It has a simple PD-like structure and can achieve an antisaturation property. In addition, with the USDE and the SMC, the robustness of the SEA system under the proposed method is obtained, while the chattering phenomenon of SMC is greatly attenuated due to the uncertainty estimation of USDE. The Lyapunov function-based theoretical analysis is present to demonstrate the stability of the closed-loop control system. Experiments are carried out to verify the effectiveness and superiority of the proposed control method.

In this paper, a real-time assistive torque controller based on sliding-mode control is proposed for a Series Elastic Actuator (SEA)-driven lower limb assistive exoskeleton. To address the problem of the lack of buffering properties and the uneven torque output in traditional exoskeletons, a novel SEA is designed for the hip joint lower-limb exoskeleton. This structure features excellent cushioning properties and smooth torque output. On this basis, to enhance the torque tracking performance of the hip joint exoskeleton, in this study, a robust composite control strategy is proposed, which can maintain accuracy in the presence of unknown external disturbances and model parameter inaccuracies. The strategy consists of an adaptive phase oscillator for outputting the phase of the gait, a single-peak curve to provide a reference assistive torque, and a low-level controller to track the torque. The low-level controller employs Continuous Sliding-Mode Control (CSMC) to obtain a continuous control law and utilizes an Extended State Observer (ESO) to estimate the lumped disturbance. It ensures that the tracking error is asymptotically convergent with minimized chatter. The closed-loop stability of the system is theoretically proven by the Lyapunov method. The validity of the proposed algorithm is validated on a designed exoskeleton.