Recent Advances in Adaptive Fractional Sliding Mode Control

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Engineering".

Deadline for manuscript submissions: closed (1 June 2024) | Viewed by 2156

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The Polytechnic School, Ira Fulton School of Engineering, Arizona State University, Mesa, AZ 85212, USA
Interests: data-driven control; fractional robust control; robotics
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Special Issue Information

Dear Colleagues,

Sliding mode control is one of the most important nonlinear robust control methods. The main part of designing sliding mode control is how to generate the sliding mode surface. Fractional calculus extends the traditional integer-order calculus by allowing the consideration of non-integer orders of differentiation and integration. This capability enables us to design an effective fractional sliding mode surface to more effectively model and control systems with fractional dynamics. This flexibility in designing an adaptive fractional sliding mode control leads to improved precision in tracking desired trajectories, robustness against external disturbances, reduced chattering phenomena, improved transient response, and reduced control effort. This method is highly encouraged for application in robotics and dynamic systems.

The focus of this Special Issue is to continue to advance research on topics relating to the theory, design, implementation, and application of fractional order systems and adaptive sliding mode control; contributions should fit the scope of the journal Fractal and Fractional, and topics of interest include (but are not limited to):

  • Fractional-order behavior modeling of robotic systems;
  • Fractional calculus applied to robotic systems;
  • Fractional-order control systems and implementation;
  • Adaptive fractional sliding mode control.

Dr. Mehran Rahmani
Guest Editor

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Keywords

  • sliding mode control
  • fractional calculus
  • robustness
  • chattering phenomena

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Published Papers (1 paper)

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Research

14 pages, 4800 KiB  
Article
Robot Manipulator Control Using a Robust Data-Driven Method
by Mehran Rahmani and Sangram Redkar
Fractal Fract. 2023, 7(9), 692; https://doi.org/10.3390/fractalfract7090692 - 18 Sep 2023
Cited by 3 | Viewed by 1754
Abstract
Robotic manipulators with diverse structures find widespread use in both industrial and medical applications. Therefore, designing an appropriate controller is of utmost importance when utilizing such robots. In this research, we present a robust data-driven control method for the regulation of a 2-degree-of-freedom [...] Read more.
Robotic manipulators with diverse structures find widespread use in both industrial and medical applications. Therefore, designing an appropriate controller is of utmost importance when utilizing such robots. In this research, we present a robust data-driven control method for the regulation of a 2-degree-of-freedom (2-DoF) robot manipulator. The nonlinear dynamic model of the 2-DoF robot arm is linearized using Koopman theory. The data mode decomposition (DMD) method is applied to generate the Koopman operator. A fractional sliding mode control (FOSMC) is employed to govern the data-driven linearized dynamic model. We compare the performance of Koopman fractional sliding mode control (KFOSMC) with conventional proportional integral derivative (PID) control and FOSMC prior to linearization by Koopman theory. The results demonstrate that KFOSMC outperforms PID and FOSMC in terms of high tracking performance, low tracking error, and minimal control signals. Full article
(This article belongs to the Special Issue Recent Advances in Adaptive Fractional Sliding Mode Control)
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