Fuzzy inferencing‐based path planning with a cyber‐physical framework and adaptive second‐order SMC for routing and mobility control in a robotic network

Nandanwar, Anuj; Nair, R.R.; Behera, Laxmidhar

doi:10.1049/iet-csr.2020.0020

Cited by 9 publications

(3 citation statements)

References 40 publications

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“…Many control schemes have been used to deal with these uncertainties such as robust control of H 2 [35] or H ∞ [36], quantitative feedback theory control method [37][38][39], and robust adaptive control law [40]. Another approach to effectively cope with these uncertainties is to estimate their upper bounds by using an adaptive approach and provide estimated data in the control law [41,42]. In [43], a combined SMC scheme and adaptive method has been utilised to design a smooth control law for a vehicle steer-by-wire system.…”

Section: Literature Reviewmentioning

confidence: 99%

Two novel approaches of adaptive finite‐time sliding mode control for a class of single‐input multiple‐output uncertain nonlinear systems

Hosseinabadi

Abadi

Mekhilef

et al. 2021

IET Cyber-Syst and Robotics

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Some systems, in spite of having multiple outputs, have only one control input, which makes their control a challenge. Two novel controllers are proposed that utilise an adaptive finite-time sliding mode control (AFSMC) scheme for a class of single-input multiple-output (SIMO) nonlinear systems in the presence of unknown mismatched uncertainties. To alleviate the inherent chattering phenomenon of sliding mode control, new forms of the two designed controllers are suggested by using new sliding surfaces. Not only can the proposed AFSMC scheme stabilise the system in a finite time, but also it can provide estimated data of the uncertainty upper bound in the controller. Lyapunov stability theory is used to obtain finite-time stability analysis of the closed-loop system. Finally, simulation results are carried out in Simulink/MATLAB for a four-dimensional autonomous hyper-chaotic system with mismatched uncertainties as an example of SIMO uncertain nonlinear systems to reveal the effectiveness of the proposed controllers.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Literature Reviewmentioning

confidence: 99%

Two novel approaches of adaptive finite‐time sliding mode control for a class of single‐input multiple‐output uncertain nonlinear systems

Hosseinabadi

Abadi

Mekhilef

et al. 2021

IET Cyber-Syst and Robotics

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“…Recognising these limitations, our study proposes a pioneering solution that integrates a digital twin model with autonomous vehicle navigation systems. This integration allows for the sophisticated simulation of real‐world conditions, enabling the system to account for ongoing infrastructure changes that could impact route optimisation [5]. Our approach utilises advanced image processing and wavelet neural networks for real‐time traffic flow predictions, further refined by a multi‐objective brainstorm optimisation (BSO) for path planning.…”

Section: Introductionmentioning

confidence: 99%

Digital twin‐based multi‐objective autonomous vehicle navigation approach as applied in infrastructure construction

Lei,

Sellers,

Luo

et al. 2024

IET Cyber-Syst and Robotics

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The widespread adoption of autonomous vehicles has generated considerable interest in their autonomous operation, with path planning emerging as a critical aspect. However, existing road infrastructure confronts challenges due to prolonged use and insufficient maintenance. Previous research on autonomous vehicle navigation has focused on determining the trajectory with the shortest distance, while neglecting road construction information, leading to potential time and energy inefficiencies in real‐world scenarios involving infrastructure development. To address this issue, a digital twin‐embedded multi‐objective autonomous vehicle navigation is proposed under the condition of infrastructure construction. The authors propose an image processing algorithm that leverages captured images of the road construction environment to enable road extraction and modelling of the autonomous vehicle workspace. Additionally, a wavelet neural network is developed to predict real‐time traffic flow, considering its inherent characteristics. Moreover, a multi‐objective brainstorm optimisation (BSO)‐based method for path planning is introduced, which optimises total time‐cost and energy consumption objective functions. To ensure optimal trajectory planning during infrastructure construction, the algorithm incorporates a real‐time updated digital twin throughout autonomous vehicle operations. The effectiveness and robustness of the proposed model are validated through simulation and comparative studies conducted in diverse scenarios involving road construction. The results highlight the improved performance and reliability of the autonomous vehicle system when equipped with the authors’ approach, demonstrating its potential for enhancing efficiency and minimising disruptions caused by road infrastructure development.

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“…The TBAC model is based on the trust evaluation technology, and determines its trustworthiness by measuring the trust value of the node, and then grants the corresponding operation authority. In this type of model, the designer sets a unified permission control strategy, and any node can make an access request, but only nodes that reach a certain trust value can pass the strategy test and obtain resources [11][12]. The basic architecture of this model is shown in Figure 2:…”

Section: Introduction To Traditional Ac Modelmentioning

confidence: 99%

Distributed System Access Control for Fuzzy Mathematics and Probability Theory

2022

DPS

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AC is to control and manage the access rights of legitimate users who enter the system on the basis of user identity authentication, so that the user's access rights are limited within the allowable range. It is an important part of information security technology. Implementing AC to users through technical means plays an important role in information security. The main purpose of this paper is to use fuzzy mathematics (FMs) and probability theory (PT) to study the access control (AC) of distributed systems (DS). This paper adds trust elements on the basis of the AC model, sets roles for each trust level, and sets a series of permissions for each role. The user determines the trust level to which he belongs by being judged by other users, and then obtains the corresponding authority through the role corresponding to the trust level. Experiments show that by evaluating the trust degree and the reputation value of user behavior, the ability of user trust degree and service and access behavior is greatly improved. Compared with the existing trust evaluation algorithm, it has a good correlation. At the same time, it satisfies the rule of "slow increase and sudden decrease" of the target change trust degree, which can effectively resist malicious users' phishing attacks, bleaching attacks, collusion attacks and other security attacks, and has higher security.

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Fuzzy inferencing‐based path planning with a cyber‐physical framework and adaptive second‐order SMC for routing and mobility control in a robotic network

Cited by 9 publications

References 40 publications

Two novel approaches of adaptive finite‐time sliding mode control for a class of single‐input multiple‐output uncertain nonlinear systems

Two novel approaches of adaptive finite‐time sliding mode control for a class of single‐input multiple‐output uncertain nonlinear systems

Digital twin‐based multi‐objective autonomous vehicle navigation approach as applied in infrastructure construction

Distributed System Access Control for Fuzzy Mathematics and Probability Theory

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