Robust nonlinear control schemes for finite-time tracking objective of a 5-DOF robotic exoskeleton

Abooee, Ali; Arefi, Mohammad Mehdi; Sedghi, Fatemeh; Abootalebi, Vahid

doi:10.1080/00207179.2018.1430379

Cited by 17 publications

(18 citation statements)

References 53 publications

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“…In addition, assume that A ∈ R 3 × 3 is a positive definite matrix. Therefore, three following inequalities ( I ), ( II ) and ( III ) expressed by (14) are always valid (Abooee and Arefi, 2019; Abooee et al, 2019).…”

Section: Basic Mathematical Conceptionmentioning

confidence: 99%

“…On the other hand, in current researches regarding the ﬁnite-time stability (Abooee and Arefi, 2018, 2019; Abooee et al, 2017, 2019; Basin, 2019; Chen and Sun, 2020; Ma et al, 2019; Yang et al, 2018; Zhao et al, 2019,), three basic control methods have been represented and established to deal with the nonlinear systems’ﬁnite-time stabilization problem, including the direct Lyapunov method, along with several applicable lemmas (Bhat and Bernstein, 1998, 2000; Feng et al, 2020; Polyakov and Poznyak, 2009), the creative method based on the geometric homogeneity conception (Bhat and Bernstein, 1998) and the terminal sliding mode control (TSMC) method (Abooee and Arefi, 2019; Abooee et al, 2017, 2019; Moradi Zirkohi, 2019; Zuo and Tie, 2014). Advantages and disadvantages of these finite-time stabilization techniques have been explained and discussed comprehensively in Abooee and Arefi (2019), Abooee et al (2017, 2019) and Sun et al (2019).…”

Section: Introductionmentioning

confidence: 98%

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Finite-time sliding mode control for a 3-DOF fully actuated autonomous surface vehicle

Abooee

Mehrizi

Arefi

et al. 2020

Transactions of the Institute of Measurement and Control

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This paper deals with the finite-time trajectory tracking problem for a typical 3-DOF (degree of freedom) autonomous surface vehicle (ASV) subjected to parametric uncertainties and environmental disturbances. Based on the nonsingular terminal sliding mode control (NTSMC) method, several separate classes of robust control inputs are designed to exactly steer all position states of the 3-DOF AVS to the desired paths during alterable finite times. By exploiting the Lyapunov stability theorem and using mathematical analysis, it is proven that all classes of designed robust control inputs are able to fulfill the mentioned finite-time tracking aim. Moreover, three applicable formulas (represented as several nonlinear inequalities) are extracted to determine the required total finite times for the suggested control schemes. Lastly, all designed control methods are numerically tested onto a benchmark 3-DOF AVS called CyberShip II. Provided computer-based numerical simulations (using MATLAB software) depicted the acceptable performance of the proposed control techniques.

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Section: Basic Mathematical Conceptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Finite-time sliding mode control for a 3-DOF fully actuated autonomous surface vehicle

Abooee

Mehrizi

Arefi

et al. 2020

Transactions of the Institute of Measurement and Control

Self Cite

View full text Add to dashboard Cite

show abstract

“…The above-mentioned robots can typically be programmed to follow specific training trajectories for a wide range of injuries. Trajectory tracking control is thus a topic of active study, and various schemes have been proposed based on it to enhance tracking performance, such as robust nonlinear control for robotic exoskeletons [7], multiple-input and multiple-output sliding mode control for gait exoskeletons [8], and redundant input safety tracking control for training walkers [9]. However, only a few of these studies have focused on utilizing randomly changeable system parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, it is more reasonable to design a controller that can train arbitrary rehabilitees. In this study, we explored a new approach based on a stochastic dynamic model (7), that can capture the random mass variations between rehabilitees. Remark 3: Our stochastic model (7), which accounts for random mass variations, is more general than the one presented in [32] (their model ( 11)).…”

Section: Introductionmentioning

confidence: 99%

“…In this study, we explored a new approach based on a stochastic dynamic model (7), that can capture the random mass variations between rehabilitees. Remark 3: Our stochastic model (7), which accounts for random mass variations, is more general than the one presented in [32] (their model ( 11)). When ∆m = 0, M s is reduced to its coefficient matrix M 0 , making its model a special case of the proposed model.…”

Section: Introductionmentioning

confidence: 99%

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Finite-time Tracking Control with Velocity Constraints for the Stochastic Rehabilitative Training Walker System Considering Different Rehabilitee Masses

Sun

Wang

Shan

2021

Preprint

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This study discusses a finite-time tracking controller for a rehabilitative training walker that imposes velocity constraints. The walker was described using a stochastic model through which the rehabilitee mass can randomly change, and a velocity constraint method was proposed to control the velocity input to every omniwheel based on a model predictive algorithm. This approach is novel in that the velocity constraint information obtained from the kinematics model was used to design the tracking controller based on the stochastic dynamic model, thus successfully constraining the actual velocity of walker as per the stochastic system. The nonlinear tracking controller was built for the stochastic rehabilitative walker to make the system’s finite time stable. Also, simulation and experiment were performed, and results confirmed that the proposed tracking control method with velocity constraints is very effective, so it may enable various rehabilitees to train safely.

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Finite-time tracking control with velocity constraints for the stochastic rehabilitative training walker systems considering different rehabilitee masses

2021

View full text Add to dashboard Cite

This study discusses a finite-time tracking controller for a rehabilitative training walker that imposes velocity constraints. The walker was described using a stochastic model through which the rehabilitee mass can randomly change, and a velocity constraint method was proposed to control the velocity input to every omniwheel based on a model predictive algorithm. This approach is novel in that the velocity constraint information obtained from the kinematics model was used to design the tracking controller based on the stochastic dynamic model, thus successfully constraining the actual velocity of walker as per the stochastic system. The nonlinear tracking controller was built for the stochastic rehabilitative walker to make the system's finite time stable. Also, simulation and experiment were performed, and results confirmed that the proposed tracking control method with velocity constraints is very effective, so it may enable various rehabilitees to train safely.

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Robust nonlinear control schemes for finite-time tracking objective of a 5-DOF robotic exoskeleton

Cited by 17 publications

References 53 publications

Finite-time sliding mode control for a 3-DOF fully actuated autonomous surface vehicle

Finite-time sliding mode control for a 3-DOF fully actuated autonomous surface vehicle

Finite-time Tracking Control with Velocity Constraints for the Stochastic Rehabilitative Training Walker System Considering Different Rehabilitee Masses

Finite-time tracking control with velocity constraints for the stochastic rehabilitative training walker systems considering different rehabilitee masses

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