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Adaptive neural control of non‐linear fractional order multi‐agent systems in the presence of error constraints and input saturation

Fatemeh Mohammadzamani, Mahnaz Hashemi, Ghazanfar Shahgholian

2022IET Control Theory and Applications35 citationsDOIOpen Access PDF

Abstract

Abstract This paper presents a tracking control problem for fractional order multi‐agent systems in the presence of uncertainties. The study takes into account the problems of error constraints, saturated inputs and transient response suitability. Because of the existing challenges, a neural adaptive control approach is used in this study. Fractional order multi‐agent systems are investigated with uncertainty in the presence of error constraints. A controller is designed on the basis of adaptive control and dynamic surface control. As a result, the control objective of pursuing the desired output is achieved in the presence of required constraints. The effective performance of the proposed controller is demonstrated by simulation using MATLAB software.

Topics & Concepts

Control theory (sociology)Saturation (graph theory)Nonlinear systemAdaptive controlArtificial neural networkComputer scienceMathematicsControl (management)Artificial intelligencePhysicsQuantum mechanicsCombinatoricsDistributed Control Multi-Agent SystemsAdaptive Control of Nonlinear SystemsAdaptive Dynamic Programming Control
Adaptive neural control of non‐linear fractional order multi‐agent systems in the presence of error constraints and input saturation | Litcius