Efficient containment control of fractional-order multi-agent systems with random perturbations and faults using interval type-II fuzzy logic

Volume 40, Issue 2, pp 226--239 https://dx.doi.org/10.22436/jmcs.040.02.06

Publication Date: July 04, 2025 Submission Date: February 25, 2025 Revision Date: April 18, 2025 Accteptance Date: May 27, 2025

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Authors

N. Iqbal - Department of Mathematics, College of Science, University of Ha’il, Ha’il 2440, Saudi Arabia. H. T. Rauf - Department of Mathematics and Statistics, University of Lahore, Sargodha 40100, Pakistan. A. U. K. Niazi - Department of Mathematics and Statistics, University of Lahore, Sargodha 40100, Pakistan. T. Saidani - Center for Scientific Research and Entrepreneurship, Northern Border University, 73213, Arar, Saudi Arabia. A. B. Rajab - Department of Computer Engineering, College of Engineering, Knowledge University, Erbil 44001, Iraq. - Department of Computer Engineering, Al-Kitab University, Altun Kupri, Iraq.

Abstract

This paper investigates the containment control problem for fractional-order nonlinear heterogeneous multi-agent systems with stochastic dynamics and actuator faults. The design of a distributed fuzzy adaptive controller will be implemented in order to cope with such large uncertainties which can be explained by all uncertain nonlinearities, stochastic interferences and limited inputs. To address the issues of uncertainty in the membership functions, the interval type-II (IT2) fuzzy set is used. Also, stochastic differential equations are used for the description of random perturbations, and actuator faults, using a fault-tolerant approach. In order to overcome these difficulties, the matrix equality and matrix inequality are used throughout the presented algorithms. The specified controller only uses information from the local neighborhood of agents; therefore, its practical implementation is unproblematic. Moreover, simulation examples are given to illustrate that the proposed control strategy is efficient and convincing.

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Keywords

• Stochastic dynamics
• input constraints
• actuator faults
• time-varying delays
• uncertainty handling
• IT-II fuzzy set
• Lyapunov-Krasovskii functional (LKF)

MSC

•  93C42
•  93C73
•  93C95
•  34K20
•  26A33

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