A Bayes estimator of parameters of nonlinear dynamic systems.
A collector for information without probability in a fuzzy setting
In the fuzzy setting, we define a collector of fuzzy information without probability, which allows us to consider the reliability of the observers. This problem is transformed in a system of functional equations. We give the general solution of that system for collectors which are compatible with composition law of the kind “inf”.
A consumption-investment problem modelled as a discounted Markov decision process
In this paper a problem of consumption and investment is presented as a model of a discounted Markov decision process with discrete-time. In this problem, it is assumed that the wealth is affected by a production function. This assumption gives the investor a chance to increase his wealth before the investment. For the solution of the problem there is established a suitable version of the Euler Equation (EE) which characterizes its optimal policy completely, that is, there are provided conditions...
A new OSS design based on parameter sensitivity to changes in measurements
A note about operations like (the weakest -norm) based addition on fuzzy intervals
We investigate a relation about subadditivity of functions. Based on subadditivity of functions, we consider some conditions for continuous -norms to act as the weakest -norm -based addition. This work extends some results of Marková-Stupňanová [15], Mesiar [18].
A note on estimation in controlled diffusion processes
A practical procedure for estimation of linear models via asymptotic quasi-likelihood.
A sample-time adjusted feedback for robust bounded output stabilization
This paper deals with a bounded control design for a class of nonlinear systems where the mathematical model may be not explicitly given. This class of uncertain nonlinear systems governed by a system of ODE with quasi-Lipschitz right-hand side and containing external perturbations as well. The Attractive Ellipsoid Method (AEM) application permits to describe the class of nonlinear feedbacks (containing a nonlinear projection operator, a linear state estimator and a feedback matrix-gain) guaranteeing...
Adaptive control scheme based on the least squares support vector machine network
Recently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified structure of LS-SVM neural networks called the multi-resolution wavelet least squares support vector machine...
Algorithms for Bayesian estimation of spline model structure
Algorithms for determining the model structure of a controlled system
An algorithm for Bayes parameter identification with quadratic asymmetrical loss function
Analysis of a nonlinear aeroelastic system with parametric uncertainties using polynomial chaos expansion.
Applications of regime-switching models based on aggregation operators
A synthesis of recent development of regime-switching models based on aggregation operators is presented. It comprises procedures for model specification and identification, parameter estimation and model adequacy testing. Constructions of models for real life data from hydrology and finance are presented.
Attitude observer-based robust control for a twin rotor system
In this paper, an angular tracking control based on adaptive super twisting algorithm (ASTA) for a Twin Rotor System is presented. With the aim of implementing the ASTA control and taking into consideration the difficulties of measuring some of its states, a Nonlinear Extended State Observer (NESO) is employed to estimate the vector state and furthermore unmeasured dynamics. This scheme increases robustness against unmodeled dynamics and external disturbance, reducing modeling difficulties due to...
Bayesian estimation of mixtures with dynamic transitions and known component parameters
Probabilistic mixtures provide flexible “universal” approximation of probability density functions. Their wide use is enabled by the availability of a range of efficient estimation algorithms. Among them, quasi-Bayesian estimation plays a prominent role as it runs “naturally” in one-pass mode. This is important in on-line applications and/or extensive databases. It even copes with dynamic nature of components forming the mixture. However, the quasi-Bayesian estimation relies on mixing via constant...
Chance constrained problems: penalty reformulation and performance of sample approximation technique
We explore reformulation of nonlinear stochastic programs with several joint chance constraints by stochastic programs with suitably chosen penalty-type objectives. We show that the two problems are asymptotically equivalent. Simpler cases with one chance constraint and particular penalty functions were studied in [6,11]. The obtained problems with penalties and with a fixed set of feasible solutions are simpler to solve and analyze then the chance constrained programs. We discuss solving both problems...
Consensus seeking in multi-agent systems with an active leader and communication delays
In this paper, we consider a multi-agent consensus problem with an active leader and variable interconnection topology. The dynamics of the active leader is given in a general form of linear system. The switching interconnection topology with communication delay among the agents is taken into consideration. A neighbor-based estimator is designed for each agent to obtain the unmeasurable state variables of the dynamic leader, and then a distributed feedback control law is developed to achieve consensus....
Constrained robust adaptive stabilization for a class of lower triangular systems with unknown control direction
This paper studies the constrained robust adaptive stabilization problem for a class of lower triangular systems with unknown control direction. A robust adaptive feedback control law for the systems is proposed by incorporating the technique of Barrier Lyapunov Function with Nussbaum gain. Such a controlled system arises from the study of the constrained robust output regulation problem for a class of output feedback systems with the unknown control direction and a nonlinear exosystem. An application...
Convergence model of interest rates of CKLS type
This paper deals with convergence model of interest rates, which explains the evolution of interest rate in connection with the adoption of Euro currency. Its dynamics is described by two stochastic differential equations – the domestic and the European short rate. Bond prices are then solutions to partial differential equations. For the special case with constant volatilities closed form solutions for bond prices are known. Substituting its constant volatilities by instantaneous volatilities we...