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International audience; In this paper, we consider dynamical graph-based systems, which are well fitted for the structural analysis of complex systems. A significant amount of work has been devoted to the controllability of such graph-based systems with application to multi-agent systems or complex networks. We give a refined analysis of the controllability through control input addition in this framework. We provide with information on the possible location of additional inputs and give tight bounds on the number of inputs to be added for controllability. These results can be easily applied to complex systems.

International audience; This paper is concerned with the study of observability in a structured framework. It turns out that the system is structurally observable if and only if the system is output connected and contains no contraction. We focus our attention on the observability preservation under sensor failure. We consider linear observable systems and we wonder if a given system remains observable in case of sensor failure. More precisely we will characterize among the sensors those which are critical \emph{i.e.} which failure leads to observability loss, those which are useless for observability purpose and the set of those which are useful without being critical. Using a graph approach we classify the sensors with respect to their importance for output connection preservation, contraction avoidance and then observability preservation under sensor failure.

The authors solve the dynamic-state-feedback block-decoupling problem in the general case, i.e. with singular or nonsingular input transformations. They prove that the problem is solvable if the number of inputs is large enough. The main tools for this study are some invariant spaces associated with the columns infinite behavior of a rotational matrix. It turns out that when the problem is solvable, it is also solvable with stability. >

In this paper we present an adaptive nonlinear speed control algorithm for induction motors. Input-output linearisation techniques are used to track torque and rotor flux and the scheme is extended for speed control. The adaptation, based on Lyapunov-design can cope with rotor and stator resistance variations while preserving stability. Exact current limitation is achieved in the known parameter case. The use of a Kalman filter, relaxes the need of rotor flux measurement. In this case no global stability proof is available. Finally only few modifications are needed for the implementation of a sampled version of the algorithm. These features are confirmed by significant simulations, that emphasise the effects of the adaptation and the observer as well as the interest of the current limitation. >

In this paper, the problem of designing an observer for linear systems with delayed state with the property that the estimated error converges to zero with a prespecified decay rate a is considered. A Luenberger-type observer for linear systems with delayed state is firstly proposed then, under certain observability conditions on the delayed-state system, criteria are proposed to ensure the a-convergence of the estimated error. Two examples are given in order to illustrate the proposed methods.

A robust adaptive regulator is designed under minimal prior knowledge, namely, the order of a nominal plant model (in a well defined sense). The involved robustness means that the closed-loop stability is guaranteed in the presence of some class of time-varying parameters and unmodeled dynamics. The main design feature of the proposed adaptive regulator consists in its self-excitation capability together with an appropriate identification-stabilization time splitting. Unlike in the available literature concerning robust adaptive control, the involved self-excitation is established independently of the parameter estimator properties. The use of the robustness-oriented modifications as deadzone and parameter projection or contraction, which are aimed at achieving the parameter estimates boundedness, is no longer required beforehand, thereby reducing the underlying prior knowledge. >

This paper presents a pole placement direct adaptive control for not necessarily minimum phase plants, which is robust with respect to unmodeled dynamics and bounded disturbances. The robustness is achieved by using both a normalized least squares algorithm with dead zone and an appropriate nonlinear feedback. The resulting closed loop system is shown to be globally stable subject to standard assumptions.