Robust control by adaptive Non-singular Terminal Sliding Mode

Asl, Reza Mohammadi; Hagh, Yashar Shabbouei; Palm, Rainer

doi:10.1016/j.engappai.2017.01.005

Cited by 76 publications

(7 citation statements)

References 45 publications

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“…Artificial intelligence (AI) [1][2][3][4][5][6][7][8] and robots [9][10][11][12][13][14][15][16][17][18][19][20] have given birth to a new wave of technological break throughs whereby the fusion of control systems with cognitive capabilities is not merely a dream but a reality that is not only being improved but also exploited with passion. The convergence is underlined by the Unscented Kalman Filter (UKF) [21][22][23][24][25][26][27][28][29][30][31][32][33], a sophisticated algorithm that has done a lot in advancing the abilities of AI-based robotics [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48]. The ability of UKF to...…”

Section: Introductionmentioning

confidence: 99%

The convergence of control and cognition: a bibliometric overview of UKF in AI-infused robotics

Obaideen,

AlShabi,

Bettayeb

et al. 2024

Disruptive Technologies in Information Sciences VIII

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This paper gives a bibliometric summary of Unscented Kalman Filter (UKF) in AI-infused robotics, highlighting its role in unifying control and cognition. Using a systematic approach that includes literature collection from IEEE Xplore, Web of Science and Google Scholar, rigorous screening and selection, and VOSviewer for a comprehensive bibliometric analysis. This analysis reports major trends, primary contributors and central themes, highlighting UKF's pivotal role in improving robotics cognitive and control capacities. The study emphasizes the universally used UKF in many fields of robotics, i.e. in navigation and mapping, sensor fusion, and state estimation, as one of its principal developers, which illustrates its vital role in promoting robotic autonomy and intelligence. The integration of findings from the bibliometric analysis thus not only presents the current state of research but also identifies possible future research directions, highlighting the increasing unification of control theories and cognitive processes in robotics. This research adds to the body of knowledge by delivering a comprehensive map of the UKF application. In this light, the UKF will be able to penetrate AI-infused robotics, the future of robotic developments will rely on the deep fusion of control and cognition facilitated by UKF and alike.

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Section: Introductionmentioning

confidence: 99%

The convergence of control and cognition: a bibliometric overview of UKF in AI-infused robotics

Obaideen,

AlShabi,

Bettayeb

et al. 2024

Disruptive Technologies in Information Sciences VIII

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“…In comparison with SMC technique, Terminal-SMC (TSMC) method presents some admirable features, such as fast convergence. In order to realize the fast convergence of states trajectories, TSMC was developed (Alattas et al, 2021; Asl et al, 2017). Terminal Sliding Mode Control scheme is the suitable for high-accuracy control because of the acceleration in rate of the convergence.…”

Section: Introductionmentioning

confidence: 99%

Finite-time convergence of perturbed nonlinear systems using adaptive barrier-function nonsingular sliding mode control with experimental validation

Mofid

Amirkhani

Din

et al. 2022

Journal of Vibration and Control

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In this study, an adaptive barrier procedure is combined with nonsingular sliding mode control (SMC) technique at the aim of the fast stabilization of nonlinear system with external disturbances. It is verified that the barred function-based control law leads to the fast convergence of state errors to a region near origin. Furthermore, the suggested method eradicates the requirement for the knowledge of upper bounds of exterior perturbations which are frequently required in SMC scheme. The stability analysis confirms fast convergence of the error states to a predetermined region. In order to demonstrate the validity of the planned method, a mass-spring system is examined as the case study. Finally, simulation and experimental outcomes on a mass-spring system are given to prove the efficacy and success of the advised methodology.

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“…Artificial Neural Networks (ANN) [1,5] are computing systems that are inspired by, but not identical to, by the functioning of the brain of living beings and they can be utilized in clustering and classification problems, and have been successfully applied in several fields, including industrial applications, stock market prediction, pattern recognition, medical diagnosis and prognosis, control tasks, etc. [20,27,33,35].…”

Section: Introductionmentioning

confidence: 99%

Efficient Thermal Comfort Estimation Employing the C-Mantec Constructive Neural Network Model

Ortega-Zamorano

Jerez

Rodríguez-Alabarce

et al. 2022

Preprint

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Thermal comfort is the condition in which a person feels satisfaction with the thermal environment through a subjective evaluation. In this work, a compact and efficient estimation of thermal comfort perception by human subjects is performed using a constructive neurocomputational model trained with data generated in controlled conditions with 49 volunteers giving 705 different scenarios, allowing, thanks to the versatility of the model, an interpretable and simple resulting function facilitating an easy handling of the results by people from different fields. The results have been compared with two of the most used standard methods for modelling thermal comfort: Fanger and COMFA models, and they show an improvement in terms of accuracy and mean square error both in a binary decision scenario (comfort or not) as well as for a discrete decision-making case in which different thermal comfort regions are considered. The flexibility of the neural model permits the incorporation of extra subject-related variables that increases further the thermal comfort estimation and, also, permits the implementation of the model in distributed and low cost/low consumption systems.

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Robust control by adaptive Non-singular Terminal Sliding Mode

Cited by 76 publications

References 45 publications

The convergence of control and cognition: a bibliometric overview of UKF in AI-infused robotics

The convergence of control and cognition: a bibliometric overview of UKF in AI-infused robotics

Finite-time convergence of perturbed nonlinear systems using adaptive barrier-function nonsingular sliding mode control with experimental validation

Efficient Thermal Comfort Estimation Employing the C-Mantec Constructive Neural Network Model

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