Marc Bordier

Key features of the electricity production sector through long-term planning : the French case

We present a view of a long-term French electricity production sector with a MARKAL approach. The aim of MARKAL is to optimise energy systems in the long- mid- term with an explicit description of the technologies used. Using the example of French electricity supply, we will illustrate the tools potential and provide the necessary technical information for assessing the extent to which MARKAL models provide a good opportunity for helping industry leaders and decision-makers who are involved in the electricity sector to make energy strategy choices-at regional, national and international level

Optimal Passive Source Localization

In order to optimize the estimation of an objects position, this paper proposes a procedure for placing acoustical sensors in 3D space, using passive source localization. A standard performance measure in estimation theory is the Cramer-Rao Lower Bound (CRLB), which describes the lower bound of the variance of unbiased estimators. In the case of passive source localization, this bound depends on the sensor and source positions, as well as on the propagation speed and the assumptions made about the disturbance noise. A procedure for an optimal sensor placement, using this CRLB as the objective function, is described. In order to assure optimal coverage of a surveillance area, the average CRLB of multiple source positions (in this area) is minimized.

Optimal sensor configuration for passive position estimation

The goal of passive source localization is to acoustically detect objects producing noises by multiple sensors (e.g. microphones, hydrophones) and to estimate their position using only the sound information. While within the last four decades a lot of work was carried out on how to best measure the time delay of arrivals (TDOAs) and on finding an optimal location estimator, relatively little work can be found on how to best place the sensors. However, the performance of such estimators is strongly correlated to the sensor configuration. Therefore, we propose a procedure for an optimal sensor setup minimizing the condition numbers of an analytic linear least-squares (LLS) estimator and an iterative, linearized model (LM) estimator. An advantage of using the condition number as the cost function is that, unlike the Cramer Rao Lower Bound, it defines an upper bound for the estimation error. Further, no assumptions about the disturbance noise need to be made and a robust sensor configuration will be found, which is invariant to rotation and dilatation. The two condition numbers of the presented passive source localization algorithms are independent of the number of sensors. However, it will be shown, that the estimation error decreases proportionally to the inverse of the square-root of the number of sensors. Some analytical forms of optimal sensor configurations will be derived, which attain the global minimum of the condition number of the LLS estimator or which minimize the condition number of the LM estimator. Further, a sensor geometry using a minimum number of sensors is derived, which forces the condition numbers of both estimators equal to one. The interest of such a setup lies in a possible combination of both estimators. The LM estimator might then be initialized by the position estimate found by the LLS estimator. A variety of alternative estimators are closely related to the LLS estimator. Their performances will be compared, and it will be shown, that the optimal sensor geometry specially derived for the LLS estimator also increases their accuracies.

Multiobjective Robust Control via Youla Parametrization

Using Youla Parametrization and Linear Matrix Inequalities (LMI) a Multiobjective Robust Control (MRC) design for continuous linear time invariant (LTI) systems with bounded uncertainties is described. The design objectives can be a combination of H∞-, H2-performances, constraints on the control signal, etc.. Based on an initial stabilizing controller all stabilizing controllers for the uncertain system can be described by the Youla parametrization. Given this representation, all objectives can be formulated by independent Lyapunov functions, increasing the degree of freedom for the control design.

An Encompassing Formalization of Robust Computed Torque Schemes of Robot Systems

This paper deals with the tracking control of robot systems in presence of perturbations such as modelling errors and disturbance forces. More specifically, this paper aims at reviewing the well-established robust computed torque controller. The first goal consists in establishing a global and encompassing formalization for a large class of robust computed torque schemes by using a Lyapunov approach. Then the second goal is to use this formalization to improve a particular scheme. It consists in deriving lower gain thresholds by exploiting the passivity property of robot systems.

Existence and boundedness of solutions of nonlinear non symmetric Riccati equations and their application in robust control Hatem Elloumi

This paper deals with nonlinear non symmetric Riccati equations which integrate a negative linear term involving a scalar gain. This type of equations is recurrent when dealing with computed torque schemes and may be used for other applications in control theory. We show that if the gain is beyond a given threshold (depending on the matrices involved in the system) then there exists a bounded solution over the whole positive times.