Neuroadaptive Performance Guaranteed Control for Multiagent Systems With Power Integrators and Unknown Measurement Sensitivity

This article investigates the adaptive performance guaranteed tracking control problem for multiagent systems (MASs) with power integrators and measurement sensitivity. Different from the structural characteristics of existing results, the dynamic of each agent is a power exponential function. A met...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2023-12, Vol.34 (12), p.9771-9782
Main Authors: Liang, Hongjing, Du, Zhixu, Huang, Tingwen, Pan, Yingnan
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive performance guaranteed control
Convergence
Exponential functions
Integrators
Mechanical systems
Multi-agent systems
Multiagent systems
Neural networks
Position errors
power integrators
Power measurement
Robot sensing systems
Sensitivity
Synchronization
Tracking control
unknown measurement sensitivity
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Summary:This article investigates the adaptive performance guaranteed tracking control problem for multiagent systems (MASs) with power integrators and measurement sensitivity. Different from the structural characteristics of existing results, the dynamic of each agent is a power exponential function. A method called adding a power integrator technique is introduced to guarantee that the consensus is achieved of the MASs with power integrators. Different from existing prescribed performance tracking control results for MASs, a new performance guaranteed control approach is proposed in this article, which can guarantee that the relative position error between neighboring agents can converge into the prescribed boundary within preassigned finite time. By utilizing the Nussbaum gain technique and neural networks, a novel control scheme is proposed to solve the unknown measurement sensitivity on the sensor, which successfully relaxes the restrictive condition that the unknown measurement sensitivity must be within a specific range. Based on the Lyapunov functional method, it is proven that the relative position error between neighboring agents can converge into the prescribed boundary within preassigned finite time. Finally, a simulation example is proposed to verify the availability of the control strategy.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2022.3160532