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Prescribed-Time Adaptive Intelligent Formation Controller for Nonlinear Multiagent Systems Based on Time-Domain Mapping

Yongming Li, Xingyan Zheng, Kewen Li

2023IEEE Transactions on Artificial Intelligence49 citationsDOI

Abstract

This paper investigates an adaptive fuzzy prescribed-time formation control problem for non-strict feedback nonlinear multi-agent systems subjected to uncertain external disturbances. Firstly, through time domain mapping, the prescribed-time formation control problem of the original system is converted to asymptotic convergence problem of the transformed system. Secondly, the fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear dynamics and the bounded estimation algorithm is utilized to design the intermediate controllers and parameter adaptive laws. Finally, by introducing an integrable function into the backstepping recursive design, an adaptive fuzzy prescribed-time formation control method is developed. Based on the Lyapunov stability theory, it is proved that the closed-loop system is stable, and the formation error converges asymptotically to zero in prescribed-time. Additionally, a numerical simulation is given to further illustrate the feasibility of the presented formation control method and theory.

Topics & Concepts

BacksteppingControl theory (sociology)Nonlinear systemController (irrigation)Bounded functionLyapunov functionAdaptive controlFuzzy logicConvergence (economics)Exponential stabilityMathematicsFuzzy control systemDomain (mathematical analysis)Lyapunov stabilityComputer scienceStability theoryMathematical optimizationControl (management)Artificial intelligenceEconomic growthPhysicsQuantum mechanicsAgronomyMathematical analysisBiologyEconomicsDistributed Control Multi-Agent SystemsAdaptive Control of Nonlinear SystemsNeural Networks Stability and Synchronization
Prescribed-Time Adaptive Intelligent Formation Controller for Nonlinear Multiagent Systems Based on Time-Domain Mapping | Litcius