In this paper, we deal with the problem of continuous-time time-varying parameter estimation in stochastic systems, under three different kinds of stochastic perturbations: additive and multiplicative white noise, and coloured noise. The proposed algorithm is based on the least squares method with forgetting factor. Some numerical examples illustrate the effectiveness of the proposed algorithm....

A mathematical model presented in this paper describes the dispersion and concentration ofcontaminants (fine and coarse) in porous medium with the effect of chemical reaction. Solutetransport in porous media is discussed by means of advection-dispersion equation. The effectof particle mass parameter and reaction rate parameter on the dispersion coefficient and meanconcentration of a chemical so...

This paper considers a quadratic stabilization problem by an H1 controller. The controller is constructed by a linear fractional transformation on contractive time-varying gains. The controller parameterization is given in terms of contractive time-varying gains. This free parameter can be used to improve the closed-loop response. A tuning method of time-varying gains is chosen so that a Lyapun...

We experimentally demonstrate and numerically simulate an adaptive method to maintain synchronization between coupled nonlinear chaotic oscillators, when the coupling between the systems is unknown and time-varying (e.g., due to environmental parameter drift). The technique is applied to optoelectronic feedback loops exhibiting high-dimensional chaotic dynamics. In addition to keeping the two s...

Parametric modeling permits an efficient representation of audio signals and is increasingly utilized for very low bit rate coding applications. Such systems are based on a decomposition of the audio signal into components that are described by appropriate source models and represented by model parameters. Commonly used components types are sinusoidal trajectories, harmonic tones, transients, a...

In this paper, we address the analysis and state-feedback synthesis problems for linear parameter-varying (LPV) systems with parameter-varying time delays. It is assumed that the state-space data and the time delays are dependent on parameters that are measurable in real-time and vary in a compact set with bounded variation rates. We explore the stability and the induced L 2 norm performance of...

A design method is presented that extends least mean squared (LMS) adaptation of time-varying parameters by including general linear time-invariant filters that operate on the instantaneous gradient vector. The aim is to track time-varying parameters of linear regression models in situations where the regressors are stationary or have slowly time-varying properties. The adaptation law is optimi...

Purpose – This paper is concerned with an online parameter estimation algorithm for nonlinear uncertain time-varying systems for which no stochastic information is available. Design/methodology/approach – The estimation procedure, called nonlinear learning rate adaptation (NLRA), computes an individual adaptive learning rate for each parameter instead of using a single adaptive learning rate fo...

Parameter estimation of time-varying non-Gaussian autoregressive processes can be a highly nonlinear problem. The problem gets even more difficult if the functional form of the time variation of the process parameters is unknown. In this paper, we address parameter estimation of such processes by particle filtering, where posterior densities are approximated by sets of samples (particles) and p...