Robust and Adaptive Control of Fractional-Order Systems, 2nd Edition

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

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 2696

Special Issue Editors


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Guest Editor
1. School of Mathematics and Physics, Guangxi Minzu University, Nanning 530006, China
2. School of Advanced Manufacturing, Sun Yat-Sen University, Guangzhou 510006, China
Interests: fractional-order system; robust control; neural network
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Guest Editor
School of Advanced Manufacturing, Sun Yat-sen University, Guangzhou 510006, China
Interests: learning control; adaptive control; robotics; fractional-order system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Many practical dynamic behaviors in the engineering field can be abstracted into fractional-order systems using fractional calculus with the unique properties of heredity and memory, e.g., gyro systems, viscoelastic systems, and many others. As an important concept in control theory, robust control focuses on stabilizing linear and nonlinear systems under modeling errors and external disturbances. Although the robust control of integer-order systems has achieved great success, the unique operational nature of fractional calculus limits the development of robust control theory for fractional-order systems. Meanwhile, adaptive control refers to a control methodology that deals with system uncertainty by adjusting certain online parameter estimates. This is an interesting way of dealing with uncertainty so that the designed controllers will usually have strong adaptation. Thus, it is expected that fractional-order systems will yield more robust and adaptive control methods.

This Special Issue pays attention to the modeling, stability analysis, robust control, adaptive control, and application of fractional-order systems. Potential topics for which submissions are encouraged include, but are not limited to, the following:

  • Modeling and simulation of fractional-order systems;
  • Dynamics and stability analysis of fractional-order systems;
  • Robust control of fractional-order systems;
  • Adaptive control of fractional-order systems;
  • Fractional-order neural networks and fuzzy systems;
  • Applications of fractional-order control methods;
  • Fuzzy and neural network control of fractional-order systems;
  • Composite learning control of fractional-order systems;
  • Adaptive synchronization of fractional-order systems.

Please feel free to read and download all publications in our 1st volume: https://www.mdpi.com/journal/fractalfract/special_issues/RACFOS

Prof. Dr. Heng Liu
Prof. Dr. Yongping Pan
Guest Editors

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Keywords

  • fractional-order system
  • stability analysis
  • adaptive control
  • robust control
  • fractional calculus

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Published Papers (2 papers)

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14 pages, 4050 KiB  
Article
Adaptive Terminal Sliding-Mode Synchronization Control with Chattering Elimination for a Fractional-Order Chaotic System
by Chenhui Wang
Fractal Fract. 2024, 8(4), 188; https://doi.org/10.3390/fractalfract8040188 - 25 Mar 2024
Cited by 2 | Viewed by 1029
Abstract
In this paper, an adaptive terminal sliding-mode control (ATSMC) method is proposed for the synchronization of uncertain fractional-order chaotic systems with disturbances. According to the sliding-mode control theory, a non-singular sliding surface is constructed. To overcome the chattering problem of ATSMC, a smooth [...] Read more.
In this paper, an adaptive terminal sliding-mode control (ATSMC) method is proposed for the synchronization of uncertain fractional-order chaotic systems with disturbances. According to the sliding-mode control theory, a non-singular sliding surface is constructed. To overcome the chattering problem of ATSMC, a smooth term is used in the controller. In order to reduce the estimation error of an uncertain parameter, adaptive laws are designed to adjust the amplitude of the continuous function. Based on the Lyapunov stability theory, a stability analysis of the error system is performed to ensure that the tracking error eventually converges to the origin. The effectiveness and applicability of the proposed control strategy are verified using the simulation results. Full article
(This article belongs to the Special Issue Robust and Adaptive Control of Fractional-Order Systems, 2nd Edition)
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21 pages, 1306 KiB  
Article
Error-Based Switched Fractional Order Model Reference Adaptive Control for MIMO Linear Time Invariant Systems
by Norelys Aguila-Camacho and Javier A. Gallegos
Fractal Fract. 2024, 8(2), 109; https://doi.org/10.3390/fractalfract8020109 - 13 Feb 2024
Cited by 2 | Viewed by 1239
Abstract
This paper presents the design and analysis of Switched Fractional Order Model Reference Adaptive Controllers (SFOMRAC) for Multiple Input Multiple Output (MIMO) linear systems with unknown parameters. The proposed controller uses adaptive laws whose derivation order switches between a fractional order and the [...] Read more.
This paper presents the design and analysis of Switched Fractional Order Model Reference Adaptive Controllers (SFOMRAC) for Multiple Input Multiple Output (MIMO) linear systems with unknown parameters. The proposed controller uses adaptive laws whose derivation order switches between a fractional order and the integer order, according to a certain level of control error. The switching aims to use fractional orders when the control error is larger to improve transient response and system performance during large disturbed states, and to obtain smoother control signals, leading to a better control energy usage. Then, it switches to the integer order when the control error is smaller to improve steady state. Boundedness of all the signals in the scheme is analytically proved, as well as convergence of the control error to zero. Moreover, these properties are extended to the case when system states are affected by a bounded non-parametric disturbance. Simulation studies are carried out using different representative plants to be controlled, showing that fractional orders and switching error levels can be found in most of the cases, such as when SFOMRAC achieves a better balance among control energy and system performance than the non-switched equivalent strategies. Full article
(This article belongs to the Special Issue Robust and Adaptive Control of Fractional-Order Systems, 2nd Edition)
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