Nacim Ramdani

Cyber-Physical Systems - Humanoid Robots - Human Robot Interaction - Interval Methods

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Dr Nacim Ramdani when awarded the HabilitationDr Nacim Ramdani has been with the Networking & Telecoms Dep. and the CERTES Lab. of the Université Paris-Est Créteil, since 1996. He currently holds the rank of Maître de Conférence - HDR (Associate Professor). He has also been affiliated with the Robotics Dep. LIRMM CNRS Univ. Montpellier 2 since 2005. During 2007-2009, he was with the INRIA Sophia Antipolis Méditerranée - the Coprin group.

He is member of the IFAC TC on Discrete Events and Hybrid System and PC member of Hybrid Systems: Computation & Control conferences. He is also co-leading the French working group on Set Computation Techniques of the French research group on Automatic Control GDR MACS, and co-organizing the annual Workshop on Interval Methods, SWIM'08 Univ. Montpellier, SWIM'09 EPFL Lausanne and SWIM'10 Nantes.

Dr Nacim Ramdani current research interests include modelling and analysis of cyber-physical systems in presence of uncertainty, set membership estimation with applications to robotics and human movement science, safe motion planning for humanoid robots, and modelling efficient / deficient human movement and posture control with applications to healthcare and human-robot interaction.

Keywords: Set membership computation, unknown-but-bounded errors, interval analysis, hybrid discrete-continuous systems, verification of safety-critical embedded systems, planning under uncertainty, motion planning for humanoid robots, human sensori-motor control, human postural control, postural coordination dynamics, rehabilitation, healthcare, aging, stroke, parametric design, parallel robots, cable-driven robots.

 

 

Newly published in Journal of Process Control 2010

Using hybrid automata for set-membership state estimation with uncertain nonlinear continuous-time systems, by N.Meslem, N.Ramdani & Y.Candau,

Abstract: This paper deals with set membership state estimation for continuous-time systems from discrete-time measurements, in the unknown but bounded error framework. The classical predictor-corrector approach to state estimation uses interval Taylor methods for solving the prediction phase, which are known to have poor performance in presence of large model or input uncertainty. In this paper, we show  how to derive more efficient predictors by using a nonlinear hybridization method which builds  hybrid automata to characterize the boundaries of reachable sets. The derived continuous-discrete set membership predictor-corrector estimator is then tested with simulated data from a bioreactor. Our method is compared to classical continuous-time interval  observers and is shown to have promising performance.

The original publication is available at www.sciencedirect.com, here doi.

Last Updated on Monday, 01 February 2010 21:28
 

Recently published in International Journal of Control, Automation, and Systems 2009

Set membership parameter estimation in the frequency domain, by T.Raïssi, N.Ramdani & Y.Candau, published in the International Journal of Control, Automation, and Systems 7(5):824–834, 2009.

Abstract: This paper is devoted to set membership parameter estimation for non-linear complex-valued models. In such a context, the error between the measured data and the output model is supposed to be bounded with known prior bounds. The proposed approach is based on set inversion via complex interval analysis. A first contribution of this paper is the extension of logarithm and exponentiel functions to polar intervals. In a second part, it is shown on an engineering application devoted to thermal parameter estimation, that the proposed interval complex representation is useful.

The original publication is available at www.springerlink.com, here 10.1007/s12555-009-0515-y

Last Updated on Sunday, 17 January 2010 22:27
 
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