H. Souley Ali

Brief Residual generator design for singular bilinear systems subjected to unmeasurable disturbances: an LMI approach

In this paper, a method to design a bank of unknown input residual generator for fault detection and isolation is investigated. The plant model is assumed to be a bounded control inputs singular bilinear systems subjected to unknown disturbances. The measurements can be bilinear.

Robust reduced order unbiased filtering for uncertain systems

This paper presents a simple solution to the robust unbiased functional reduced order filtering problem in the case of uncertain systems described by Integral Quadratic Constraint (IQC). The existence condition of the unbiased filter is expressed through a rank relation. Then the filter is designed via Linear Matrix Inequalities coupled with an equality constraint. The results obtained in this paper are applicable to unstable systems. The approach is illustrated by a numerical example.

Robust filter design for polytopic systems

This paper presents, in both continuous and discrete-time cases, a solution to the robust H/sub /spl infin// and L/sub 2/ - L/sub /spl infin// functional reduced order filtering problem via LMI methods for uncertain polytopic systems. After giving necessary and sufficient conditions for the existence and the stability of the unbiased filter in the nominal case, the result is extended to derive a robust filter. The problem is transformed into a static output feedback one and is solved by LMI.

REDUCED-ORDER FILTER FOR STOCHASTIC BILINEAR SYSTEMS WITH MULTIPLICATIVE NOISE

This paper deals with the design of a reduced-order H-infinty filter for a stochastic bilinear systems with a prescribed H-infinty norm criterion. The problem is transformed into the search of a unique gain matrix by using a Sylvester-like condition on the drift term. The considered system is bilinear in control and with multiplicative noise in the state and in the measurement equations. The approach is based on the resolution of LMI and is then easily implementable.

STOCHASTIC ROBUST REDUCED ORDER H-INFINITY OBSERVER-BASED CONTROL

Abstract This paper considers robust reduced order H ∞ observer-based control for stochastic systems. The approach is divided into two steps. First, we search for a linear control law to ensure H ∞ specification. Then, the obtained linear combination of the state is used to solve an “unbiasedness” (decoupling) condition on the drift part of the closed-loop system. Finally, deterministic functional filtering techniques are applied to obtain the observer-based controller.

H-INFINITY FILTERING FOR A CLASS OF STOCHASTIC BILINEAR SYSTEMS WITH MULTIPLICATIVE NOISE

Abstract In this paper, the purpose is to design a filter for a stochastic bilinear system which satisfies an H ∞ prescribed norm constraint and such that the estimation error is mean-square stable. The system under consideration is bilinear in control input and is subjected to multiplicative noise in both the state and the measurement equations. The system is also corrupted by deterministic perturbations. The proposed approach is based on the resolution of LMI and the filter design requires to satisfy a rank condition.

ROBUST H-INFINITY REDUCED ORDER FILTERING F OR UNCER TAIN BILINEAR SYSTEMS

Abstract This paper investigates ℋ ∞ reduced order unbiased filtering problems for a nominal bilinear system and a bilinear system affected by norm-bounded structured uncertainties in all the system matrices. First, the unbiasedness condition is derived. Second, a change of variable is introduced on the inputs of the system to reduce the conservatism inherent to the filter stability requirement and to treat the product of the inputs by the disturbances. Then the solution is expressed in terms of LMI by transforming the problem into a robust state feedback in the nominal case and a robust static output feedback in the uncertain case.

Reduced order unbiased filtering for a class of uncertain bilinear systems

This paper presents a simple solution to the /spl Hscr//sub /spl infin// unbiased functional reduced order filtering problem via linear matrix inequality (LMI) methods for bilinear systems. We extend the result to the robust filtering for bilinear systems subject to structured norm-bounded time-varying uncertainties. After giving conditions for the existence of the unbiased filter in the nominal case, we show that the filter design is reduced to a small gain problem in the nominal case and to a static output feedback one when the nominal bilinear system is affected by the uncertainties.