Abstract
Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging affect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the quality of treatment. Amongst recent control strategies used for rehabilitation robots, active disturbance rejection control (ADRC) strategy is a systematic way out from a robust control paradox with possibilities and promises. In this modern era, we always try to find the solution in order to have minimum resources and maximum output, and in robotics-control, to approach the same condition observer-based control strategies is an added advantage where it uses a state estimation method which reduces the requirement of sensors that is used for measuring every state. This paper introduces improved active disturbance rejection control (I-ADRC) controllers as a combination of linear extended state observer (LESO), tracking differentiator (TD), and nonlinear state error feedback (NLSEF). The proposed controllers were evaluated through simulation by investigating the sagittal plane gait trajectory tracking performance of two degrees of freedom, Lower Limb Robotic Rehabilitation Exoskeleton (LLRRE). This multiple input multiple output (MIMO) LLRRE has two joints, one at the hip and other at the knee. In the simulation study, the proposed controllers show reduced trajectory tracking error, elimination of random, constant, and harmonic disturbances, robustness against parameter variations, and under the influence of noise, with improvement in performance indices, indicates its enhanced tracking performance. These promising simulation results would be validated experimentally in the next phase of research.
Highlights
Results are compared for PID and active disturbance rejection control (ADRC), for the hip and knee trajectories based on error comparison the results show a better performance of ADRC over PID
Amongst all the controllers ADRC-nonlinear state error feedback (NLSEF)-tracking differentiator (TD) proves a better selection because of its best tracking capabilities followed by ADRC-TD and ADRC-NLSEF, prove it as a promising strategy
The performance indices Integral time square error (ITSE), Integral time absolute error (ITAE), IAE, Integral square error (ISE), and Integral square of the control signal (ISU) reflects the potential of proposed ADRC combinations over ADRC in terms of trajectory tracking, control signal requirement, and disturbance rejection, under the influence of noise and parametric variation
Summary
The physiotherapist’s job is to assist the patient in performing various rehabilitative tasks, and help them to recover or improve natural strength and movements through a set of objective oriented exercises. There is no quantitative analysis for the patient’s recuperation that can be acquired subsequent to the performance of rehabilitative exercises. Robotic rehabilitation devices can be ameliorated in such cases to overcome the difficulties of therapeutic training [3,4] as they are designed for the purpose of objective oriented tasking and can frequently work on the same trajectory for the duration of time depending on the patient’s comfort. The performance tracking after the training through these devices leads to reinforcing the recovery of the patient, where, validation can be established by improvement comparison on the measurement result
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