Cristobal Ochoa-Luna

In this paper, we present a backstepping approach integrated with time-delay estimation to provide an accurate estimation of unknown dynamics and to compensate for external bounded disturbances. The control was implemented to perform passive rehabilitation movements with a 7-DOF exoskeleton robot named ETS-Motion Assistive Robotic-Exoskeleton for Superior Extremity. The unknown dynamics and external bounded disturbances can affect the robotic system in the form of input saturation, time-delay errors, friction forces, backlash, and different upper-limb's mass of each subject. The output of the time-delay estimator is coupled directly to the control input of the proposed adaptive tracking control through a feed-forward loop. In this case, the control system ensures a highly accurate tracking of the desired trajectory, while being robust to the uncertainties and unforeseen external forces, and flexible with variation of parameters. Due to the proposed strategy, the designed control approach does not require accurate knowledge of the dynamic parameters of the exoskeleton robot to achieve the desired performance. The stability of the exoskeleton robot and the convergence of its state errors are established and proved based on Lyapunov-Krasovskii functional theory. Experimental results and a comparative study are presented to validate the advantages of the proposed strategy.

This paper presents two rehabilitation schemes for patients with upper limb impairments. The first is an active-assistive scheme based on the trajectory tracking of predefined paths in Cartesian space. In it, the system allows for an adjustable degree of variation with respect to ideal tracking. The amount of variation is determined through an admittance function that depends on the opposition forces exerted on the system by the user, due to possible impairments. The coefficients of the function allow the adjustment of the degree of assistance the robot will provide in order to complete the target trajectory. The second scheme corresponds to active movements in a constrained space. Here, the same admittance function is applied; however, in this case, it is unattached to a predefined trajectory and instead connected to one generated in real time, according to the user's intended movements. This allows the user to move freely with the robot in order to track a given path. The free movement is bounded through the use of virtual walls that do not allow users to exceed certain limits. A human-machine interface was developed to guide the robot's user.

SUMMARY: Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach.