Passive and active rehabilitation control of human upper-limb exoskeleton robot with dynamic uncertainties

Abstract

SUMMARYThis paper investigates the passive and active control strategies to provide a physical assistance and rehabilitation by a 7-DOF exoskeleton robot with nonlinear uncertain dynamics and unknown bounded external disturbances due to the robot user's physiological characteristics. An Integral backstepping controller incorporated with Time Delay Estimation (BITDE) is used, which permits the exoskeleton robot to achieve the desired performance of working under the mentioned uncertainties constraints. Time Delay Estimation (TDE) is employed to estimate the nonlinear uncertain dynamics of the robot and the unknown disturbances. To overcome the limitation of the time delay error inherent of the TDE approach, a recursive algorithm is used to further reduce its effect. The integral action is employed to decrease the impact of the unmodeled dynamics. Besides, the Damped Least Square method is introduced to estimate the desired movement intention of the subject with the objective to provide active rehabilitation. The controller scheme is to ensure that the robot system performs passive and active rehabilitation exercises with a high level of tracking accuracy and robustness, despite the unknown dynamics of the exoskeleton robot and the presence of unknown bounded disturbances. The design, stability, and convergence analysis are formulated and proven based on the Lyapunov–Krasovskii functional theory. Experimental results with healthy subjects, using a virtual environment, show the feasibility, and ease of implementation of the control scheme. Its robustness and flexibility to deal with parameter variations due to the unknown external disturbances are also shown.

Mechatronic Design of a Robot for Upper Limb Rehabilitation at Home

“…EMG sensors to detect muscle stimuli) also one can considered other rehabilitation motions or control strategies, as proposed for example in Refs. [26][27][28].…”

A Novel Exoskeleton with Fractional Sliding Mode Control for Upper Limb Rehabilitation

“…The homogenous transformation matrix that represents frame {7} with respect to frame {0} can be obtained by multiplying individual transformation matrices. 0 7 T = 0 1 T. 1 2 T 2 3 T. 3 4 T. 5 T. 5 6 T. 6 7 T = ⎡ ⎢ ⎣ r11 r12 r13 Px r21 r22 r23 Py r31 r32 r33 Pz…”

Novel adaptive backstepping control for uncertain manipulator robots using state and output feedback

“…Besides, robot's structural knowledge is further needed to identify and quantify robot's dynamic model [18]. A promising solution is to use a time delay estimation (TDE) [19,20] to approximate such uncertainties. This is achieved by introducing a fixed artificial time delay and then utilizing prior data to approximate system's unknown dynamics and uncertainties.…”

“…This is achieved by introducing a fixed artificial time delay and then utilizing prior data to approximate system's unknown dynamics and uncertainties. However, in real time, state derivative feedbacks, such as velocity and acceleration, of the manipulator robot are not explicitly available, which are necessary to compute TDE's control law [19,20]. A common practice is to estimate such derivative variables by numerically differentiating the position response.…”

“…A common practice is to estimate such derivative variables by numerically differentiating the position response. In most cases, this response, however, contains a lot of noise, which causes measurement errors and thus degrades control accuracy [19,20]. Other employed solutions include decentralized control approaches [17,21].…”