Applications of Fractional Operators in Robotics: A Review

Chávez-Vázquez, S.; Gómez-Aguilar, J. F.; Lavín-Delgado, J. E.; Escobar-Jiménez, R.F.; Olivares-Peregrino, Víctor Hugo

doi:10.1007/s10846-022-01597-1

Cited by 25 publications

(17 citation statements)

References 193 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It allows them to recognize objects, people, and other visual cues and respond accordingly. Here can see an example of an intelligent robot with a computer [15]. Visioning in Fig 2 . A four-wheel robot with sensors and a camera Picture of a Four-wheel Robot with sensors and a camera (example of an intelligent robot with computer visioning) 5.3 Natural language processing (NLP): NLP helps robots to understand and respond to human language.…”

Section: Leading Technologies For the Development Of Intelligent Robotmentioning

confidence: 99%

A Review on the Emerging Developments in Ai: Robotics

Uzair,

Khan

2023

IJEAST

View full text Add to dashboard Cite

The development of intelligent robots is a complex process that requires careful consideration of various factors. The key to creating a successful intelligent robot is to define its purpose, select the right hardware, develop robust software, implement machine learning algorithms, ensure safety, test extensively, and continuously improve its capabilities. By following these suggestions, developers can create intelligent robots that can perform a range of tasks, learn from their environment, and adapt to new situations. Intelligent robots have the potential to revolutionize various industries by improving efficiency, safety, and productivity. Intelligent robots also can operate in hazardous environments where human workers would be at risk, such as in nuclear power plants, oil refineries, and other industrial settings. The review provides guidance, updates, and issues in the development of the intelligent robot.

show abstract

Section: Leading Technologies For the Development Of Intelligent Robotmentioning

confidence: 99%

A Review on the Emerging Developments in Ai: Robotics

Uzair,

Khan

2023

IJEAST

View full text Add to dashboard Cite

show abstract

“…The theory of fractional-order (Fo) calculus, which has been around for the past three centuries and deals with derivatives and integrals of non-integer order [ 9 , 10 , 11 , 12 , 13 ], was recently rediscovered by scientists and engineers and is being utilized in various domains such as material sciences [ 14 ], bioengineering [ 15 ], finance [ 16 ], and electronic circuits [ 17 , 18 ], including the field of control theory [ 19 , 20 , 21 , 22 , 23 , 24 ]. The numerous control techniques such as proportional–integral–derivative (PID) control, the SMC method, and various fuzzy and neural network schemes have all implemented their respective control techniques using a Fo controller [ 25 , 26 , 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

Design of Adaptive Fractional-Order Fixed-Time Sliding Mode Control for Robotic Manipulators

Ahmed

Azar

Tounsi

2022

Entropy

View full text Add to dashboard Cite

In this investigation, the adaptive fractional-order non-singular fixed-time terminal sliding mode (AFoFxNTSM) control for the uncertain dynamics of robotic manipulators with external disturbances is introduced. The idea of fractional-order non-singular fixed-time terminal sliding mode (FoFxNTSM) control is presented as the initial step. This approach, which combines the benefits of a fractional-order parameter with the advantages of NTSM, gives rapid fixed-time convergence, non-singularity, and chatter-free control inputs. After that, an adaptive control strategy is merged with the FoFxNTSM, and the resulting model is given the label AFoFxNTSM. This is done in order to account for the unknown dynamics of the system, which are caused by uncertainties and bounded external disturbances. The Lyapunov analysis reveals how stable the closed-loop system is over a fixed time. The pertinent simulation results are offered here for the purposes of evaluating and illustrating the performance of the suggested scheme applied on a PUMA 560 robot.

show abstract

“…Ndaïrou et al [21] reported on the mathematical and numerical analysis of a fractional Caputo differential system that approximates the infectious individuals of COVID-19. Some other valuable work on the application of fractional calculus can be found in [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Numerical Solution of Two-Dimensional Time Fractional Mobile/Immobile Equation Using Explicit Group Methods

Salama

Ali

2022

Int. J. Appl. Comput. Math

View full text Add to dashboard Cite

In this paper, we shall present the development of two explicit group schemes, namely, fractional explicit group (FEG) and modified fractional explicit group (MFEG) methods for solving the time fractional mobile/immobile equation in two space dimensions. The presented methods are formulated based on two Crank-Nicolson (C-N) finite difference schemes established at two different grid spacings. The stability and convergence of order O(τ 2−α + h 2 ) are rigorously proven using Fourier analysis. Several numerical experiments are conducted to verify the efficiency of the proposed methods. Meanwhile, numerical results show that the FEG and MFEG algorithms are able to reduce the computational times and iterations effectively while preserving good accuracy in comparison to the C-N finite difference method.

show abstract

Applications of Fractional Operators in Robotics: A Review

Cited by 25 publications

References 193 publications

A Review on the Emerging Developments in Ai: Robotics

A Review on the Emerging Developments in Ai: Robotics

Design of Adaptive Fractional-Order Fixed-Time Sliding Mode Control for Robotic Manipulators

Numerical Solution of Two-Dimensional Time Fractional Mobile/Immobile Equation Using Explicit Group Methods

Contact Info

Product

Resources

About