Functional observers design for nonlinear discrete-time systems with interval time-varying delays

summary:This paper is concerned with the functional observer design for a class of Multi-Input Multi-Output discrete-time systems with mixed time-varying delays. Firstly, using the Lyapunov-Krasovskii functional approach, we design the parameters of the delay-dependent observer. We establish the sufficient conditions to guarantee the exponential stability of functional observer error system. In addition, for design purposes, delay-dependent sufficient conditions are proposed in terms of matrix inequalities to guarantee that the functional observer error system is exponentially stable. Secondly, we presented the sufficient conditions of the existence of internal-delay independent functional observer to ensure the estimated error system is asymptotically stable. Furthermore, some sufficient conditions are obtained to guarantee that the internal-delay independent functional observer error system is exponentially stable. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed method

Observer synthesis under time-varying sampling for Lipschitz nonlinear systems

International audienceIn this work, the problem of observation of continuous-time nonlinear Lipschitz systems under time-varying discrete measurements is considered. This class of systems naturally occurs when continuous processes are observed through digital sensors and information is sent via a network to a computer for state estimation. Since the network introduces variations in the sampling time, the observer must be designed so that it takes them into account. Here impulsive observers, which make instantaneous correction when information is received, are investigated. Moreover, we consider time-varying observer gains adapting to the varying sampling interval. In order to deal with both continuous-time and discrete-time dynamics, a new hybrid model is used to state the problem and establish the convergence of the proposed observer. First, generic conditions are provided using a hybrid Lyapunov function. Then, a restriction of the generic Lyapunov function is used to establish tractable conditions that allows the analysis and synthesis of an impulsive gain

New Bounds for State Transition Mat.

International audienceWe address the problem of constructing matrix-valued interval observers for estimating state transition matrices for time-varying systems. We provide less conservative estimators than those in recent literature. We cover continuousand discrete-time linear systems, under Metzler or nonnegativity conditions on the coefficient matrices. We show how to satisfy our Metzler conditions after simple changes of coordinates. We illustrate our method using a feedback stabilized underwater marine robotic dynamics with unknown control gains

New Bounds for State Transition Matrices

International audienceWe address the problem of constructing matrix-valued interval observers for estimating state transition matrices for time-varying systems. We provide less conservative estimators than those in recent literature. We cover continuous-and discrete-time linear systems, under Metzler or nonnegativity conditions on the coefficient matrices. We show how to satisfy our Metzler conditions after simple changes of coordinates. We illustrate our method using a feedback stabilized underwater marine robotic dynamics with unknown control gains

Design of Interval Observers for Estimation and Stabilization of Discrete-Time LPV Systems

International audienceThis work is devoted to interval observers design for discrete-time Linear Parameter-Varying (LPV) systems under the assumption that the vector of scheduling parameters is not available for measurements. Two problems are considered: a pure estimation problem and an output stabilizing feedback design problem where the stability conditions are expressed in terms of Linear Matrix Inequalities (LMIs). The efficiency of the proposed approach is demonstrated through computer simulations

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version