Robust Model-Free Control for Robot Manipulator under Actuator Dynamics

Elleuch, Dorsaf; Damak, Tarak

doi:10.1155/2020/7417314

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…A lot of model-free control methods were developed in the literature, such as time delay-based control (TDC) [16,17] and intelligent proportional derivative integral controllers (iPD/iPI/iPID) [18,19]. In spite of the independence of these model-free controllers on the dynamic model and its easiness in implementation, the inserted constant delay may degrade the control performance of time delay-based control TDC [20].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fractional‐Order Super‐Twisting Sliding Mode Controller for Lower Limb Rehabilitation Exoskeleton in Constraint Circumstances Based on the Grey Wolf Optimization Algorithm

Faraj

Maalej

Derbel

et al. 2023

Mathematical Problems in Engineering

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In this work, a lower limb exoskeleton with uncertainties and external disturbances under constrained motion has been controlled by developing a model-free adaptive optimal fractional-ordersuper-twisting sliding mode (AOFSTSM) controller. Contrary to popular existing modeling methods, the modeling of the lower limb exoskeleton has been accomplished in the case of contact with the ground. A fractional-order operator and super-twisting sliding mode control have been combined to achieve an excellent tracking performance, chatter-free control inputs, and robustness to external disturbances and uncertainties. The controller structure is model-independent which has been derived without needing to know the dynamics of the system. An adaptive control strategy has been adopted as an approximating method to evaluate the uncertain dynamics of the system without the necessity for knowing the prior knowledge of the upper bounds. A grey wolf optimization technique has been used to find the optimal values of controller parameters. The stability of the overall system has been investigated and derived from the Lyapunov stability criterion. To validate the effectiveness of our proposed controller structure, a series of comparative simulations have been conducted with optimal fractional-order super-twisting sliding mode (OFSTSM) controller and fractional-order super-twisting sliding mode (FSTSM) controller. The comparative simulations have been also carried out with other types of recently existing control methods and recently existing optimization algorithms. The results of numerical simulations indicate the superiority of the AOFSTSM controller over other types of recently existing optimization algorithms and controllers in terms of tracking error and robustness towards the uncertainties and external disturbances.

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Section: Introductionmentioning

confidence: 99%

Adaptive Fractional‐Order Super‐Twisting Sliding Mode Controller for Lower Limb Rehabilitation Exoskeleton in Constraint Circumstances Based on the Grey Wolf Optimization Algorithm

Faraj

Maalej

Derbel

et al. 2023

Mathematical Problems in Engineering

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“…Machine learning-based controllers including neural networks and fuzzy logic approaches are also designed in this context [25]. A data-driven observerbased model-free adaptive discrete-time terminal SMC [26], an extended state observer-based controller [27], the PID control [28], [29] and an intelligent proportional-derivative SMC [30] have also been designed as model-free controllers. The designed model-free controllers mostly consist of a controller plus estimated robot dynamics, i.e., the alternative model-free controllers have virtually the same structure as the PD plus gravity controller, but they have more complicated control design procedures and their control performances are not significantly better than the PD plus gravity controller.…”

Section: Introductionmentioning

confidence: 99%

A model-free continuous integral sliding mode controller for robust control of robotic manipulators

Ablay

2023

IJRA

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<p>This paper proposes a model-free continuous integral sliding mode controller for robust control of robotic manipulators. The highly nonlinear dynamics of robots and load disturbances cause control challenges. To achieve tracking control under load disturbances and nonlinear parameter variations, the controller is constructed with three continuous terms including an integral term that acts as an adaptive controller. The proposed controller is able to accomplish a non-overshoot transient response, a short settling time, and strong disturbance rejection performance for robotic manipulators. The developed model-free control method is implemented on the PUMA 560 robotic manipulator, and its performance is compared with the proportional-derivative (PD) plus gravity controller. Numerical results under measurement noise and load disturbances are provided in order to show the efficacy, validity, and feasibility of the method.</p>

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Intelligent iPD control estimation of Hardware in-the-Loop generated dynamics

Martínez García,

Soria López

2024

iit

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We are concerned here by the study of explicit ultra-local model approximation in the context of model free intelligent Proportional Derivative (iPD) control, which to our knowledge has not been reported in the available control literature. The unmodeled dynamics estimation is approximated by integrals reducing real-time system measurements noise in the control loop and implemented using a Finite Impulse Response (FIR) digital filter. Hardware-in-the-Loop (HIL) perturbation load generated dynamics are used in an iPD control scheme exhibiting the unknown dynamics approximation. We use two DC servo motors interconnected by their shafts. The first DC servo motor is controlled by the proposed feedback-based iPD controller whereas the second DC servomotor is used as a programmable torque load to the controlled DC servo motor. Using HIL testing we can generate desired load torques directly showing how the iPD controller approximates HIL generated perturbations. For the proposed control iPD scheme, we present both computer-based simulation and experimental real-time control results.

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Robust Model-Free Control for Robot Manipulator under Actuator Dynamics

Cited by 4 publications

References 19 publications

Adaptive Fractional‐Order Super‐Twisting Sliding Mode Controller for Lower Limb Rehabilitation Exoskeleton in Constraint Circumstances Based on the Grey Wolf Optimization Algorithm

Adaptive Fractional‐Order Super‐Twisting Sliding Mode Controller for Lower Limb Rehabilitation Exoskeleton in Constraint Circumstances Based on the Grey Wolf Optimization Algorithm

A model-free continuous integral sliding mode controller for robust control of robotic manipulators

Intelligent iPD control estimation of Hardware in-the-Loop generated dynamics

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