Controlling chaos in nuclear spin generator system using backstepping design.
Decomposition of vibration signals into deterministic and nondeterministic components and its capabilities of fault detection and identification
The paper investigates the possibility of decomposing vibration signals into deterministic and nondeterministic parts, based on the Wold theorem. A short description of the theory of adaptive filters is presented. When an adaptive filter uses the delayed version of the input signal as the reference signal, it is possible to divide the signal into a deterministic (gear and shaft related) part and a nondeterministic (noise and rolling bearings) part. The idea of the self-adaptive filter (in the literature...
Design of spline-based self-tuners
Detection and accommodation of second order distributed parameter systems with abrupt changes in input term: Existence and approximation
The purpose of this note is to investigate the existence of solutions to a class of second order distributed parameter systems with sudden changes in the input term. The class of distributed parameter systems under study is often encountered in flexible structures and structure-fluid interaction systems that use smart actuators. A failure in the actuator is modeled as either an abrupt or an incipient change of the actuator map whose magnitude is a function of the measurable output. A Galerkin-based...
Errata: ``A simple mathematical model of the human liver''
Erratum of article “Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems”
Erratum of article “Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems”
Estimation of functions of a dependent variable
Exact modelling of scalar 2D arrays
Fuzzy adaptive control of a class of MISO nonlinear systems
Fuzzy feedback linearizing controller and its equivalence with the fuzzy nonlinear internal model control structure
This paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodology, two popular control structures, namely, feedback linearization and Nonlinear Internal Model Control...
Generalized kernel regression estimatefor the identification of Hammerstein systems
A modified version of the classical kernel nonparametric identification algorithm for nonlinearity recovering in a Hammerstein system under the existence of random noise is proposed. The assumptions imposed on the unknown characteristic are weak. The generalized kernel method proposed in the paper provides more accurate results in comparison with the classical kernel nonparametric estimate, regardless of the number of measurements. The convergence in probability of the proposed estimate to the unknown...
Gradient Method as a Tool for Mathematical Modeling in Earthquake Engineering
Graphical model selection for a particular class of continuous-time processes
Graphical models provide an undirected graph representation of relations between the components of a random vector. In the Gaussian case such an undirected graph is used to describe conditional independence relations among such components. In this paper, we consider a continuous-time Gaussian model which is accessible to observations only at time . We introduce the concept of infinitesimal conditional independence for such a model. Then, we address the corresponding graphical model selection problem,...
Hamiltonian identification for quantum systems: well-posedness and numerical approaches
This paper considers the inversion problem related to the manipulation of quantum systems using laser-matter interactions. The focus is on the identification of the field free Hamiltonian and/or the dipole moment of a quantum system. The evolution of the system is given by the Schrödinger equation. The available data are observations as a function of time corresponding to dynamics generated by electric fields. The well-posedness of the problem is proved, mainly focusing on the uniqueness of the...
Hysteresis nonlinearity identification using new Preisach model-based artificial neural network approach.
Identifiability and estimation of pharmacokinetic parameters for the ligands of the macrophage mannose receptor
The aim of this paper is numerical estimation of pharmacokinetic parameters of the ligands of the macrophage mannose receptor, without knowing it a priori the values of these parameters. However, it first requires a model identifiability analysis, which is done by applying an algorithm implemented in a symbolic computation language. It is shown that this step can lead to a direct numerical estimation algorithm. In this way, a first estimate is computed from noisy simulated observations without it...
Identification and estimation of parameters in abstract Cauchy problems.
Identification d'un phénomène bactériologique
Identification of a quasilinear parabolic equation from final data
We study the identification of the nonlinearities A,(→)b and c appearing in the quasilinear parabolic equation y_t − div(A(y)∇y + (→)b(y)) + c(y) = u inΩ × (0,T), assuming that the solution of an associated boundary value problem is known at the terminal time, y(x,T), over a (probably small) subset of Ω, for each source term u. Our work can be divided into two parts. Firstly, the uniqueness of A,(→)b and c is proved under appropriate assumptions. Secondly, we consider a finite-dimensional optimization...