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Mean-Square Output Consensus of Heterogeneous Multi-Agent Systems with Multiplicative Noises in Dynamics and Measurements

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Abstract

This paper studies the output consensus problem of heterogeneous linear stochastic multiagent systems with multiplicative noises in system parameters and measurements, where the system noise in each agent is allowed to be different. By employing stochastic output regulation theory and the stochastic Lyapunov function approach, a composite controller embedded with stochastic output regulator equations (SOREs) and a stochastic dynamic compensator is designed to achieve the mean-square output consensus of the multi-agent systems. To implement the consensus algorithm, a sufficient condition for feasible solutions of the SOREs is first established in terms of Lyapunov and Selvester equations. Then the time-varying SOREs are approximated by the Euler-Maruyama method combined with an a-posteriori partial estimation of the increments of the Brownian motion. A numerical example illustrates the theoretical results.

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Correspondence to Shixian Luo.

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This research was supported by the National Natural Science Foundation of China under Grant Nos. 62003104 and 62003103, the Guangxi Science and Technology Planning Project under Grant No. AD23026217, the Guangxi Natural Science Foundation under Grant No. 2022GXNSFBA035649, the Interdisciplinary Scientific Research Foundation of Guangxi University under Grant No. 2022JCC019, and the Guangxi University Natural Science and Technological Innovation Development Multiplication Plan Project under Grant No. 2023BZRC018.

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Lin, B., Luo, S. & Jiang, Y. Mean-Square Output Consensus of Heterogeneous Multi-Agent Systems with Multiplicative Noises in Dynamics and Measurements. J Syst Sci Complex 36, 2364–2381 (2023). https://doi.org/10.1007/s11424-023-2281-y

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  • DOI: https://doi.org/10.1007/s11424-023-2281-y

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