Marcio De Queiroz


Roy O. Martin Lumber Company Professor of Mechanical Engineering

Coordinator of the Robotics Engineering Program and Minor

3250C Patrick F. Taylor Hall

Department of Mechanical & Industrial Engineering

Louisiana State University

Baton Rouge, LA 70803


Innovation in Control and Robotics Engineering (iCORE) Lab Website

Educational Background

  • Ph.D., Electrical Engineering, Clemson University, 1997
  • M.S., Mechanical Engineering, Pontifical Catholic University of Rio de Janeiro, Brazil, 1993
  • B.S., Electrical Engineering, Federal University of Rio de Janeiro, Brazil, 1990

Research Overview

My general area of expertise is dynamic systems and control. Within this general area, my primary focus is on the theory and application of nonlinear control systems. On the theory side, I am interested in the development of new nonlinear control algorithms as well as new stability analysis tools for nonlinear systems. Since control is fundamentally an application‐driven discipline, I am equally interested in pursuing real‐world uses for these design and analysis tools. Throughout my career, I have worked on a variety of control engineering applications, including robotic systems, biological/biomedical systems, active bearings, and aerospace systems.


I am currently interested in the concept of formation control of multi-agent systems using tools from rigid graph theory. We have developed a control design framework that is applicable to different agent models (single integrator, double integrator, and dynamic) and different formation problems (static and dynamic formation acquisition, formation maneuvering, and target interception). Our formation control algorithms were recently tested on UGVs in collaboration with Dr. Matthew Feemster of United States Naval Academy. Efforts are also underway to test them on UAVs for the purpose of creating mobile, remote sensing networks for agricultural and environmental applications.

Selected Publications

S. Ramazani, R. Selmic, and M. de Queiroz, “Rigidity-Based Multi-Agent Layered Formation Control,” IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2016.2568164, in press.

P. Zhang, M. de Queiroz, and X. Cai, “3D Dynamic Formation Control of Multi-Agent Systems Using Rigid Graphs,” ASME Journal of Dynamic Systems, Measurement, and Control, Vol. 137, No. 11, Paper No. 111006, 2015.

X. Cai and M. de Queiroz, “Formation Maneuvering and Target Interception for Multi-Agent Systems via Rigid Graphs,” Asian Journal of Control, Vol. 17, No. 4, pp. 1174-1186, 2015.

X. Cai and M. de Queiroz, “Adaptive Rigidity-Based Formation Control for Multi-Robotic Vehicles with Dynamics,” IEEE Transactions on Control Systems Technology, Vol. 23, No. 1, pp. 389-396, 2015.

I. Karafyllis, M. Malisoff, M. de Queiroz, M. Krstic, and R. Yang, “Predictor-Based Tracking for Neuromuscular Electrical Stimulation,” International Journal of Robust and Nonlinear Control, Vol. 25, pp. 2391-2419, 2015.

X. Cai and M. de Queiroz, “Rigidity-Based Stabilization of Multi-Agent Formations,” ASME Journal of Dynamic Systems, Measurement, and Control, Vol. 136, No. 1, Paper No. 014502, 2014.

G. Meades Jr., X. Cai, N.K. Thalji, G.L. Waldrop, and M. de Queiroz, “Mathematical Modeling of Negative Feedback Regulation by Carboxyltransferase,” IET Systems Biology, Vol. 5, No. 3, pp. 220–228, 2011.

M.S. de Queiroz, D.M. Dawson, S. Nagarkatti, and F. Zhang, Lyapunov-Based Control of Mechanical Systems, Cambridge, MA: Birkhäuser, ISBN 0-8176-4086-X, 2000.