Fractional order PID controller tuned by bat algorithm for robot trajectory control

Faraj, Mohammad A.; Abbood, Abdulsalam M.

doi:10.11591/ijeecs.v21.i1.pp74-83

Cited by 19 publications

(11 citation statements)

References 21 publications

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“…f a represents the control feed, and n represents the control spindle speed. Based on the above control servo mixed parameters, the control matrix [9] can be quickly generated, and the effective dual servo valve drive control strategy f can be obtained by using the transparency recombination method, as shown in (4) below.…”

Section: ( ) ( ) ( ) O Jw P Jw I Jw =mentioning

confidence: 99%

A study on the dual servo valve drive control method for fully automatic hydraulic heavy-duty manipulators

Wang

2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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Aiming at the problems of high energy consumption and large tracking error in the dual servo valve drive control of fully automatic hydraulic heavy-duty manipulator, a dual servo valve drive control method for fully automatic hydraulic heavy-duty manipulator was studied. Based on the two port theory, generate a dual servo valve drive control strategy for a fully automatic hydraulic heavy-duty robotic arm. Taking control accuracy and control response time as necessary conditions for servo control, control inference simulation, design a dual servo valve drive controller for fully automatic hydraulic heavy-duty manipulator, and achieve dual servo valve drive control for fully automatic hydraulic heavy-duty manipulator. The experimental results show that the average control tracking errors of the A-level and B-level dual servo valve drivers of the proposed method are 0.1386m and 0.1434m, respectively, and the average servo drive energy consumption is 1.4257×10 4 J and 1.5257×10 4 J has good control performance, can reduce driving control energy consumption, and reduce tracking errors.

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Section: ( ) ( ) ( ) O Jw P Jw I Jw =mentioning

confidence: 99%

A study on the dual servo valve drive control method for fully automatic hydraulic heavy-duty manipulators

Wang

2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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“…Theorem 1. If the sliding mode dynamics (27) and the control law (29) are developed and combined, then it will guarantee the stability of the LLE system converging to the origin along with s � 0. Proof.…”

Section: Fractional-order Super-twisting Sliding Mode (Fstsm)mentioning

confidence: 99%

“…In the last three decades, fractional-order (FO) calculus (which is a process of developing a general form of integerorder integration and diferentiation to noninteger-order one) has become an important issue adopted by mathematicians, engineers, and scientists [27,28]. Tanks to the benefts of using a fractional calculus represented by providing more fexibility for improving the control performance, adding an extra degree of freedom to the controller's structure, diferent FO controllers were formulated to enhance the control performance of nonlinear systems, such as fractional PID controllers [29], FO neural network controllers [30], and FO adaptive controllers [31,32].…”

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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“…Various types of of LLE have been manufactured and constructed by different universities and research centers such as Lokomat [4], berkeley lower extremity exoskeleton (BLEEX) [5] and active leg exoskeleton (ALEX) [6]. Different control strategies have been introduced in order to track predeterminded trajectory for nonlinear robotics systems such as: active disturbance rejection control [7], fractional order control [8], robust control [9] and sliding mode control (SMC) [10].…”

Section: Introductionmentioning

confidence: 99%

Optimal sliding mode controller for lower limb rehabilitation exoskeleton in constrained environments

Faraj

Maalej

Derbel

2023

IJEECS

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<p>In this article, a lower limb exoskeleton (LLE) under contacting constrained motion has been modelled using augmented Lagrange equations which include Lagrange multiplier and Jacobian vectors. A sliding mode Controller optimized by the grey Wolf optimization algorithm has been used for controlling (LLE) in the case of constrained motion with uncertainties and outside perturbation. The grey wolf optimization algorithm has been used as an optimization algorithm for finding the optimal controllers’ parameters in order to improve the performance of the system. The stability analysis of the closed-loop system has been performed using Lyapunov theory of stability. To validate the effectiveness of the proposed controller structure grey wolf optimization algorithm controller (GW-SMC), a series of comparative simulations have been carried out with other types of recently existing sliding mode control (SMC). The results of numerical simulations indicate the superiority of the sliding mode optimized by the GW-SMC over other types of recently existing controller in terms of tracking errors and robustness towards uncertainties and external disturbances.</p>

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Fractional order PID controller tuned by bat algorithm for robot trajectory control

Cited by 19 publications

References 21 publications

A study on the dual servo valve drive control method for fully automatic hydraulic heavy-duty manipulators

A study on the dual servo valve drive control method for fully automatic hydraulic heavy-duty manipulators

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

Optimal sliding mode controller for lower limb rehabilitation exoskeleton in constrained environments

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