Robustness and Tracking Performance Evaluation of PID Motion Control of 7 DoF Anthropomorphic Exoskeleton Robot Assisted Upper Limb Rehabilitation

Abstract

Upper limb dysfunctions (ULD) are common following a stroke. Annually, more than 15 million people suffer a stroke worldwide. We have developed a 7 degrees of freedom (DoF) exoskeleton robot named the smart robotic exoskeleton (SREx) to provide upper limb rehabilitation therapy. The robot is designed for adults and has an extended range of motion compared to our previously designed ETS-MARSE robot. While providing rehabilitation therapy, the exoskeleton robot is always subject to random disturbance. Moreover, these types of robots manage various patients and different degrees of impairment, which are quite impossible to model and incorporate into the robot dynamics. We hypothesize that a model-independent controller, such as a PID controller, is most suitable for maneuvering a therapeutic exoskeleton robot to provide rehabilitation therapy. This research implemented a model-free proportional–integral–derivative (PID) controller to maneuver a complex 7 DoF anthropomorphic exoskeleton robot (i.e., SREx) to provide a wide variety of upper limb exercises to the different subjects. The robustness and trajectory tracking performance of the PID controller was evaluated with experiments. The results show that a PID controller can effectively control a highly nonlinear and complex exoskeleton-type robot.

Flatness tracking control scheme of rehabilitation exoskeleton robot with dynamic uncertainties

“…where r(q) contains terms of the order 1 and I m is the (m 3 m) identity matrix. Now, from equations ( 8) to (12), and the fact that the partial derivative (∂(E 1 , . .…”

“…Researchers have developed many different control strategies for manipulating such robots, with various theoretical and practical contributions. [8][9][10][11] In addition, many other techniques have been proposed for this type of exoskeleton systems to provide a passive form of rehabilitation such as a proportional-integraldifferential classical control, 12 impedance control 13 and computed torque control. 14 In reality, the presence of unknown dynamics of the exoskeleton robot and unknown bounded disturbances due to the robot user's physiological characteristics prevents the robot from correctly following the defined path.…”

Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot

“…In particular, the motor function of the upper limb is greatly affected, rendering individuals unable to perform activities of daily living independently. Restoring the functional ability of the upper limbs in patients with disabilities is imperative, as individuals require the use of their upper limbs to carry out various daily activities [2]. As per the neuroplasticity hypothesis, consistent and intensive training can modify the structure and function of the nervous system and restore the connection between the affected limb and the injured central nerve of the brain, thereby regaining control over the limb's motor function [3].…”

“…Compared to previous studies, the main contributions of this research can be summarized as follows: (1) This study proposes a fuzzy adaptive passive controller based on a potential field that is designed according to the desired motion trajectory, which can provide a normal force pointing towards the desired trajectory. (2) The controller uses the subject's task performance and impulses as evaluation indices of the subject's motor ability. (3) The controller adaptively adjusts the stiffness coefficient of the potential field using fuzzy logic, thereby adaptively changing the magnitude of the assisting force.…”

Control predictivo para el seguimiento de trayectorias en un exoesqueleto de asistencia en la rehabilitación de movilidad articular en la mano

“…Las estrategias de control se implementan para proporcionar diferentes formas de terapia de rehabilitación, incluida la terapia pasiva, activa y asistida activa. Dependiendo del objetivo de la rehabilitación, se puede emplear varios controladores para lograr la meta, como el control de la posición, el control de fuerza o el control de torque [56][57][58][59][60]. En las terapias pasivas, los ejercicios son realizados por medio de un comando de entrada al controlador, sin intervención del usuario [57,[60][61][62][63].…”