TY  - JOUR
Y1  - 2022///
PB  - MDPI
SN  - 20763417
JF  - Applied Sciences (Switzerland)
A1  - Aole, S.
A1  - Elamvazuthi, I.
A1  - Waghmare, L.
A1  - Patre, B.
A1  - Bhaskarwar, T.
A1  - Meriaudeau, F.
A1  - Su, S.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123420931&doi=10.3390%2fapp12031287&partnerID=40&md5=c8a5711735ff7af4e7f273bc99bd0435
VL  - 12
AV  - none
N2  - In this paper, a combined control strategy with extended state observer (ESO) and finite time stable tracking differentiator (FTSTD) has been proposed to perform flexion and extension motion repetitively and accurately in the sagittal plane for shoulder and elbow joints. The proposed controller improves the tracking accuracy, performs state estimation, and actively rejects disturbance. A sinusoidal trajectory as an input has been given to a two-link multiple-input multiple-output (MIMO) upper limb robotic rehabilitation exoskeleton (ULRRE) for a passive rehabilitation purpose. The efficacy of the controller has been tested with the help of performance indices such as integral time square error (ITSE), integral square error (ISE), integral time absolute error (ITAE), and integral of the absolute magnitude of error (IAE). The system model is obtained through the Eulerâ??Lagrangian method, and the controllerâ??s stability is also given. The proposed controller has been simulated for ±20 parameter variation with constant external disturbances to test the disturbance rejection ability and robustness against parametric uncertainties. The proposed controller has been compared with already developed ESO-based methods such as active disturbance rejection control (ADRC), nonlinear active disturbance rejection control (NLADRC), and improved active disturbance rejection control (I-ADRC). It has been found that the proposed method increases tracking performance, as evidenced by the above performance indices. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
N1  - cited By 7
IS  - 3
ID  - scholars17125
TI  - Active Disturbance Rejection Control Based Sinusoidal Trajectory Tracking for an Upper Limb Robotic Rehabilitation Exoskeleton
ER  -