Adaptive Fractional High‐order Terminal Sliding Mode Control for Nonlinear Robotic Manipulator under Alternating Loads

Ahmed, Saim; Wang, Haoping; Tian, Yang

doi:10.1002/asjc.2354

Cited by 51 publications

(42 citation statements)

References 27 publications

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“…Note that compared to the traditional centralized adaptive FTC approaches for one single system, 13,17,32–35 the proposed adaptive update laws (17)–(20) can estimate the unknown parameters using the neighbor’s information of states.…”

Section: Resultsmentioning

confidence: 99%

Distributed fault-tolerant formation control for multiple unmanned aerial vehicles under actuator fault and intermittent communication interrupt

Han

Jiang

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article develops a distributed adaptive fault-tolerant formation control scheme for the multiple unmanned aerial vehicles to counteract actuator faults and intermittent communication interrupt, where the issues on control input saturation and mismatched uncertainties are also addressed. The discontinuous communication protocol technique is exploited to achieve the stability of the formation system, if the conditions of dwell time and the rate of communication are satisfied. On the basis of the local information of neighboring unmanned aerial vehicles, a novel distributed adaptive mechanism is designed to estimate the bounds of actuator faults and uncertainties, where the input saturation is explicitly taken into consideration. The stability of the whole formation system under the designed fault-tolerant formation control strategy is analyzed using the Lyapunov approach. Finally, simulation results are presented to illustrate the effectiveness of the proposed scheme.

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Section: Resultsmentioning

confidence: 99%

Distributed fault-tolerant formation control for multiple unmanned aerial vehicles under actuator fault and intermittent communication interrupt

Han

Jiang

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…According to equation (17), 0 \ r ł 1 and l . l min , there must be a constant l \ 1 that makes the following statement true…”

Section: Stability Analysismentioning

confidence: 99%

“…14 In order to improve the response characteristics of the system and attenuate the uncertainties, the developed robust model-free controller incorporates time delay control (TDC) as well as adaptive terminal sliding mode control (ATSMC) methods. 15 The robust adaptive fractional-order nonsingular fast terminal sliding mode control (RFO-TSMC) 16 is introduced by Ahmed et al In order to obtain the trajectory tracking of robotic manipulators under varying loads with uncertainties and external disturbances, the adaptive fractional high-order terminal sliding mode control (AFO-HoTSMC) 17 is proposed by Ahmed et al Some of these methods have been applied to practical problems.…”

Section: Introductionmentioning

confidence: 99%

Anti-noise model-free adaptive control and its application in the circulating fluidized bed boiler

Dong

Zhu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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Model-free adaptive control has been developed greatly since it was proposed. Up to now, model-free adaptive control theory has become mature and tends to be an effective solution for complex unmodeled industrial systems. In practical industrial processes, most control systems are inevitably accompanied by noise that will result in indelible error and may further cause inaccurate feedback to the output. In order to solve this kind of problem with model-free technique, this article incorporates an improved tracking differentiator into model-free adaptive control. After that, the anti-noise model-free adaptive control method with complete convergence analysis is proposed. Meanwhile, numerical simulation proves that the improved control method can quickly track a given signal with good resistance to noise interference. Finally, the effectiveness and practicability of the proposed algorithm are verified by experiments through the control of drum water level of circulating fluidized.

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“…However, human objects or weapon detection and tracking are still conducted at cloud centers, as real-time, online tracking is computationally costly. Significant efforts have been made in recent years to monitor robot manipulators that need high control performance in reliability and speed [9,10].…”

Section: Introductionmentioning

confidence: 99%

Weapon Detection Using YOLO V3 for Smart Surveillance System

Narejo

Pandey

Vargas

et al. 2021

Mathematical Problems in Engineering

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Every year, a large amount of population reconciles gun-related violence all over the world. In this work, we develop a computer-based fully automated system to identify basic armaments, particularly handguns and rifles. Recent work in the field of deep learning and transfer learning has demonstrated significant progress in the areas of object detection and recognition. We have implemented YOLO V3 “You Only Look Once” object detection model by training it on our customized dataset. The training results confirm that YOLO V3 outperforms YOLO V2 and traditional convolutional neural network (CNN). Additionally, intensive GPUs or high computation resources were not required in our approach as we used transfer learning for training our model. Applying this model in our surveillance system, we can attempt to save human life and accomplish reduction in the rate of manslaughter or mass killing. Additionally, our proposed system can also be implemented in high-end surveillance and security robots to detect a weapon or unsafe assets to avoid any kind of assault or risk to human life.

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Adaptive Fractional High‐order Terminal Sliding Mode Control for Nonlinear Robotic Manipulator under Alternating Loads

Cited by 51 publications

References 27 publications

Distributed fault-tolerant formation control for multiple unmanned aerial vehicles under actuator fault and intermittent communication interrupt

Distributed fault-tolerant formation control for multiple unmanned aerial vehicles under actuator fault and intermittent communication interrupt

Anti-noise model-free adaptive control and its application in the circulating fluidized bed boiler

Weapon Detection Using YOLO V3 for Smart Surveillance System

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