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Research Papers

Cooperative Optimal Synchronization of Networked Uncertain Nonlinear Euler–Lagrange Heterogeneous Multi-Agent Systems With Switching Topologies

[+] Author and Article Information
A. R. Mehrabian

Department of Electrical and
Computer Engineering,
Concordia University,
Montreal, QC H3G 1M8, Canada
e-mail: armehrabian@gmail.com

K. Khorasani

Department of Electrical and
Computer Engineering,
Concordia University,
Montreal, QC H3G 1M8, Canada
e-mail: kash@ece.concordia.ca

A similar argument has appeared in the proof of Theorem 7 in Ref. [34].

1Present address: Senior Flight Control Systems Designer, TRU Simulation and Training, A Textron Company, Montreal, QC, Canada.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received November 24, 2013; final manuscript received September 17, 2014; published online November 7, 2014. Assoc. Editor: Yongchun Fang.

J. Dyn. Sys., Meas., Control 137(4), 041006 (Apr 01, 2015) (12 pages) Paper No: DS-13-1468; doi: 10.1115/1.4028687 History: Received November 24, 2013; Revised September 17, 2014

This paper is concerned with design of distributed optimal synchronization control strategies for a class of networked nonlinear heterogeneous multi-agent (HMA) systems whose dynamics are governed by Euler–Lagrange (EL) equations. We employ optimal control techniques to design synchronization (consensus seeking) and set-point regulation controllers for HMA systems through optimization of individual cost functions. We introduce an analytical solution to the optimization problem and show that the developed optimal control laws can manage switchings in the communication network topology. Additionally, we propose two control strategies (namely, adaptive and robust) to modify and generalize the developed optimal control laws in presence of parametric uncertainties in the HMA systems. Simulation results for the attitude synchronization control of a network of eight spacecraft are presented to demonstrate the effectiveness and capabilities of our proposed control algorithms.

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Figures

Grahic Jump Location
Fig. 2

The states of the eight networked spacecraft under our proposed adaptive synchronization controller. The dotted red line represents the reference set-point that is only available to the network leaders, i.e., the spacecraft #1 and #6.

Grahic Jump Location
Fig. 3

The states of the eight networked spacecraft under our proposed robust synchronization controller. The dotted red line represents the reference set-point that is only available to the network leaders, i.e., the spacecraft #1 and #6.

Grahic Jump Location
Fig. 4

The control efforts of the eight networked spacecraft under our proposed adaptive synchronization controller

Grahic Jump Location
Fig. 5

The control efforts of the eight networked spacecraft under our proposed robust synchronization controller

Grahic Jump Location
Fig. 1

The three communication network topologies that are considered in the simulations according to the Definition 1. HMA systems that are shown by a square are the leaders and the ones that are shown by a circle are the followers.

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