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This paper addresses the problem of static output feedback synthesis and focuses on H2 optimisation. The bilinear problem of finding a control feedback gain K and a Lyapunov matrix P is shown to be equivalent to a BMI problem that involves slack variables and a state feedback gain. This BMI condition is a promising theoretical result that links the two state and output feedback questions in a unified...
This paper is concerned with the stability and control of linear systems with uncertain physical parameters. The case where the characteristic equations of the systems are polynomially dependent on uncertain parameters is studied. A new algorithm is presented for the calculation of stability margins in the parameter space in general / p-norms. The stability is defined with respect to a desired region...
This paper addresses the problem of stability robustness of minimum-phase nonlinear dynamical systems modeled with feedforward neural networks with bounded parametric uncertainties under IOF linearization. By means of an affine description of the feedforward neural network model which takes into account the parametric uncertainties, the Input-Output Feedback (IOF) linearization is performed and the...
In this paper, the regional pole placement is studied. An analysis of robustness with respect to unstructured uncertainty, being 2-norm bounded, for linear systems is discussed. A bound on the maximum allowable perturbation is proposed. Moreover, a useful parameterization of such bound, based on the structure of the gain matrix and on a novel formula for computing the eigenvectors of any real matrix,...
A new method is proposed for the solution of linear matrix inequalities over a finite horizon for linear discrete time varying systems with or without uncertainties. The method is used to solve a variety of problems beginning with the standard H∞ discrete-time bounded real lemma and extending through to robust H∞ general-filtering and output-feedback control design of uncertain systems. In the latter...
For both continuous and discrete-time cases, this paper presents a simple solution to the robust H∞ unbiased functional reduced order filtering problem via LMI methods in the presence of norm-bounded time-varying uncertainties. Necessary and sufficient conditions for the existence and the stability of the unbiased filter are given in the nominal case; the filter differs from that of 11] (only nominal...
In this paper, numerical optimisation in combination with a suitable parametrisation of all stable closed-loop systems is proposed as a tool for control structure selection. The key benefit is that the suitability of a control structure can be assessed without a priori information about the desired closed-loop behaviour or the controller structure. Thus, it constitutes an effective tool to explore...
This paper addresses robust H∞ static output feedback control problem for multimodel systems with time-varying normbounded uncertainties. Sufficient conditions for synthesis of a static output feedback controller are derived in terms of a set of linear matrix inequalities (LMIs). The effectiveness of the proposed design method is demonstrated by an example for the control of a multimodel constituted...
The paper consider some special topics related to controllability of linear switching systems. Consequences of the normal controllability property and controllability under sampling are investigated. Both problems are related to the existence of a finite switching sequence with certain properties. It is shown that completely controllable linear switching systems, regardless to the sign of the allowed...
The method of sample-based minimax optimization is developed for the minimization problem with an uncertain quadratic objective function subject to linear constraints. Several examples based on confidence statistical estimation are considered to define the uncertainty set. Analytical and numerical techniques are proposed for finding the optimal robust strategy.
In this paper a recursive technique, based on the subspace state space identification methods, is presented for identification of time-varying systems. The main idea was to develop an iterative algorithm with most of the advantages of this kind of methods in order to deal with real-time applications and minimize the computational burden. As a subspace-based state space system identification technique,...
In this paper wo prosont a now methodology, based on dynamic inversion, for the set-point constrained regulation of a scalar linear system with structured uncertainties. The approach basically relies on the combined design of the controller and of the reference command input. The first is based on LQR methodology whilst the latter is determined by means of a stable dynamic inversion. An illustrative...
New algorithms are presented for the computation of good upper and lower bounds on the structured singular value μ, for high order plants subject to purely real or mixed real/complex uncertainty. A geometric form of the Hahn-Banach theorem is used to develop an algorithm for computing an upper bound on μ, involving a linear program and a symmetric eigenvalue problem at each iteration. A proof of convergence...
A fault isolation observer is developed for failure detection and isolation of multiple faults in discrete-time dynamic systems. The design of freedom remaining available after directional residuals generation is used to satisfy an H ∞ disturbance attenuation constraint.
An architecture for fault tolerant feedback controllers based on the Youla parameterization is suggested. It is shown that the Youla parameterization will give a residual vector directly in connection with the fault diagnosis part of the fault tolerant feedback controller. It turns out that there is a separation between the feedback controller and the fault tolerant part. The closed loop feedback...
Adaptive filters with suitable nonlinear devices are very effective in suppressing the adverse effect due to impulse noise. In a previous work, the authors have proposed a new class of nonlinear adaptive filters using the concept of robust statistics [1,2]. The robust M-estimator is used as the objective function, instead of the mean square errors, to suppress the impulse noise. The optimal coefficient...
In this note we extend the design tool presented in [6] for robust stabilization of nonminimum-phase nonlinear systems to the case of output regulation problems. As in [6] we take advantage from a design tool known in the linear literature as “vibrational feedback” to handle the presence of unstable zero dynamics in output regulation problems in presence of uncertainties. This work frames in a research...
This paper proposes an original solution for the observation of nonlinear uncertain systems. Features of this observer based on high order sliding modes are a finite and a priori known convergence time, robustness against unstructured (even unmatched) uncertainties and limited chattering. This is, as far as the authors known, the first observer structure which garantees an a priori known convergence...
A fast and robust algorithm for the separation of complex valued signals is presented. It is assumed that the original, complex valued source signals are mutually statistically independent, and that the mixing process is linear. The problem is solved by the independent component analysis (ICA) model. ICA is a statistical method for transforming an observed multidimensional random vector into components...
In this paper we present a new control approach based on both: Linear Matrix Inequalities and Sliding Mode Control. This strategy is applied to interconnected systems which consider local disturbances (matched and unmatched disturbances) together with local and remote uncertainties. The proposed approach guarantees global stability by using only an output feedback. The control law is composed by two...
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