Dynamic-free robust adaptive intelligent fault-tolerant controller design with prescribed performance for stable motion of quadruped robots

Farid, Yousef; Majd, Vahid Johari; Ehsani-Seresht, Abbas

doi:10.1177/1059712319890692

Cited by 10 publications

(5 citation statements)

References 45 publications

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“…Remark 1. From equation (11), both the value of x3 j j and x4 j j are related to k 24 ; therefore, the value of k 24 can be made larger on the premise that equation ( 9) is satisfied, so as to reduce the upper bound of the convergence error. So it is easy to find D 3 , D 4 that satisfy Assumption 3 and Horwitz stability.…”

Section: Design Of Aiesomentioning

confidence: 99%

“…After a fault is detected, the controller should compensate for the fault in time to maintain system performance. Researchers have proposed many FTC strategies, such as adaptive control, 10 intelligent control, 11 neural network control, 12 and so on. Because sliding mode control has the advantage of being insensitive to the total disturbance in the system, many literatures propose FTC algorithms based on sliding mode control.…”

Section: Introductionmentioning

confidence: 99%

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Fault-tolerant control of second-order systems based on augmented improved extended state observer and non-singular high-order fast terminal sliding mode

Yang

Liu

Wen

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this article, a fault-tolerant control method based on augmented improved extended state observer and non-singular high-order fast terminal sliding mode is proposed for a class of second-order systems with actuator faults. First, the initial peak of the traditional extended state observer is avoided by improving the structure of the observer. Second, the total disturbance and its change trend are observed simultaneously, so as to better realize the compensation of total disturbance. The convergence of the observer is proved theoretically. In addition, by designing non-singular high-order fast terminal sliding mode surface, the sliding mode variable converges rapidly during the whole process to improve the algorithm’s rapidity. Finally, the chattering of control signal caused by sliding mode control is greatly reduced using high-order sliding mode technology, and the stability of the whole closed-loop system is proved by Lyapunov criterion. The comparative experimental results on the fault-tolerant control platform of the quadrotor unmanned aerial vehicle demonstrate the effectiveness and superiority of the proposed observer and controller.

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Section: Design Of Aiesomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fault-tolerant control of second-order systems based on augmented improved extended state observer and non-singular high-order fast terminal sliding mode

Yang

Liu

Wen

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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show abstract

“…When the friction between the foot and the slope ground is less than the component of gravity, the robot will slip and cannot continue to move on the slope. Therefore, the maximum angle that a quadruped crawling robot can bear when it moves on the slope depends on the friction coefficient µ (Farid et al , 2021) between the foot and the slope. The walking environment of the robot studied in this paper is a slope of 15°≤ θ ≤30°, and here a 20°slope is selected for research.…”

Section: Recognition Of Slope Environmentmentioning

confidence: 99%

Research on obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition

Wang

Song

Renquan

et al. 2022

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Purpose Aiming at the problem that quadruped crawling robot is easy to collide and overturn when facing obstacles and bulges in the process of complex slope movement, this paper aims to propose an obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition. Design/methodology/approach First, considering the problem of low uniformity of feature points in terrain recognition images under complex slopes, which leads to too long feature point extraction time, an improved ORB (Oriented FAST and Rotated BRIEF) feature point extraction method is proposed; second, when the robot avoids obstacles or climbs over bumps, aiming at the problem that the robustness of a single step cannot satisfy the above two motions at the same time, the crawling gait is planned according to the complex slope terrain, and a robot obstacle avoidance gait planning based on the artificial potential field method is proposed. Finally, the slope walking experiment is carried out in the Robot Operating System. Findings The proposed method provides a solution for the efficient walking of robot under slope. The experimental results show that the extraction time of the improved ORB extraction algorithm is 12.61% less than the original ORB extraction algorithm. The vibration amplitude of the robot’s centroid motion curve is significantly reduced, and the contact force is reduced by 7.76%. The time it takes for the foot contact force to stabilize has been shortened by 0.25 s. This fact is verified by simulation and test. Originality/value The method proposed in this paper uses the improved feature point recognition algorithm and obstacle avoidance gait planning to realize the efficient walking of quadruped crawling robot on the slope. The walking stability of quadruped crawling robot is tested by prototype.

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“…Zhang et al (2022) investigated an iterative learning approach integrated with adaptive sliding-mode control method to accomplish passive rehabilitation therapy tasks for wearable 6 degrees of freedom upper-limb exoskeleton with unknown dynamic parameters and non-periodic disturbance. An alternative solution to cope with model uncertainties is using neural networks (NNs) (Chen et al, 2021a; Farid et al, 2019; Rahmani et al, 2016). NNs have been employed to approximate the unknown parameters of the quadruped robots with input dead-zone (Zhang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous locomotion and manipulation control of quadruped robots using reinforcement learning-based adaptive fractional-order sliding-mode control

Farid

2023

Transactions of the Institute of Measurement and Control

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This paper investigates a model-free reinforcement learning-based approach that enables the quadruped robot to manipulate objects while maintaining its balance and dynamic stability during walking. At first, the dynamics of quadruped robots in two sub-spaces, position control space and force control space, are developed. Then, a new long-term performance index is introduced, and a radial basis function neural network as a critic network is presented to estimate the unobtainable long-term performance index. Based on the exported reinforcement signal, the actor neural network is introduced to generate the feedforward compensation term to cope with the nonlinear dynamics and the system uncertainties. The robustness of the actor-critic reinforcement learning algorithm is enhanced by using a fractional-order sliding-mode controller in the closed-loop system. The online adaptive laws for both the critic and actor-network weights are obtained using the Lyapunov stability theory. As a result, the uniformly ultimately boundedness of the position and the force tracking errors are proven. Finally, numerical simulations are conducted to illustrate the feasibility and effectiveness of the proposed adaptive actor-critic learning-based control scheme.

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Dynamic-free robust adaptive intelligent fault-tolerant controller design with prescribed performance for stable motion of quadruped robots

Cited by 10 publications

References 45 publications

Fault-tolerant control of second-order systems based on augmented improved extended state observer and non-singular high-order fast terminal sliding mode

Fault-tolerant control of second-order systems based on augmented improved extended state observer and non-singular high-order fast terminal sliding mode

Research on obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition

Simultaneous locomotion and manipulation control of quadruped robots using reinforcement learning-based adaptive fractional-order sliding-mode control

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