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The stability of filters for nonlinear dynamic systems with Lipschitz nonlinearities is addressed. By considering the disturbances in the system and measurement equations as the inputs to the system representing the estimation error dynamics, the input-output stability of the filtering mapping associated with the estimation error dynamics is introduced. This is done with respect to signals belonging...
The theoretic ground of a locally topological method for defining a minimal attractor embedding dimension on the basis of linear and nonlinear decompositions in state-space of a dynamic system is proposed. The computer confirmation of the theoretical results is presented.
Estimation of structure and motion in computer vision systems can be performed using a dynamic systems approach, where states and parameters in a perspective system are estimated. This paper presents a new approach to the structure estimation problem, where the estimation of the 3D-positions of feature points on a moving object is reformulated as a parameter estimation problem. For each feature point,...
This paper presents a new method for symbol estimation in the downlink of a CDMA communication system. Our approach is based on the observation that the slowly-fading CDMA signal model may be expressed as a linear combination of the convolved independent symbol sequences. A blind source separation approach based on maximization of output entropy is used for the blind separation of the sources; the...
In this paper, different techniques for the estimation of the signal parameters and/or the channel coefficients for single-input/multiple-output systems, arc presented. These methods arc based, cither on the use of a small part of observations or on the minimization of a quadratic form with quadratic constraint. Simulations have been established and these techniques arc compared to the classical approaches.
The paper proposes an alternative way to solve robust reference tracking problem. Instead of rejecting the effect of the disturbance directly, an intermediate step is built into the state estimation problem. The advantage of the methodology is to elaborate a modified optimal state estimation problem taking the unbiased estimate of the disturbance into account. Henceforward, the solution of the discrete...
By using robust control techniques, this paper proposes an adaptive control for rigid robots with the following important features: under a parameter-dependent PE (Persistent Excitation) condition, it gives a guaranteed transient performance of tracking a smooth desired trajectory while assuring the parameter estimation error to go to a residual set of the origin arbitrarily fast. Simulations are...
This paper introduces a mesh-based motion estimation scheme for image sequences and nodal motion vectors optimization by using a multi-resolution differential method. Because our final aim is mesh tracking throughout a video sequence, neither backward tracking nor forward tracking is well suited. The backward tracking provides good results when simply applied to two successive images, but it is damaged...
The problem of nonlinear processing of nongaussian and noncoherent signals is common in many applications such as remote sensing, hydroacoustics, radioastronomy and communication technologies. Optimal solution of this problem requires taking into account the space-time statistical properties of signals, medium and noise, which are usually known a priori. One of the best methods is suggested by the...
In this work we present a new algorithm to solve the average-consensus problem. The main goal of this algorithm is to obtain exact convergence despite the existence of quantized communication channels between the agents. Starting from the Zoom-in Zoom-out strategy already presented in [5], we introduce the equations describing the behaviour of the algorithm and we formally prove the asymptotic agreement...
An inverse method is developed to recover for unknown stochastic inputs. The proposed approach relies on an approximate finite impulse response model of the system which is seen as a linearization around the current input estimation. The inversion itself is done within the frequency domain in order to lower the computation cost. This classical approach requires a regularization technique to be used...
In this paper, the author proposes an algorithm of dual predictive control for a system expressed by a linear ARX (auto-regressive and exogenous) model with uncertain plant model parameters. Previously, the author proposed a dual predictive control algorithm which first considered the uncertainties in future control input values and in future output values included in an ARX model. The future input...
Probability Density Functions defined on IR+ can be successfully modeled with the help of the Mellin Transform : this rather underrated transform is well suited for such functions so that we propose the new definitions of "second kind" characteristic functions based on this transform. By this way, second kind moments and second kind cumulants can also be defined, so that multiplicative noise,...
A model-based fault management system for a Three Mass Torsion Oscillator is described. Fault management includes fault detection, fault diagnosis and fault compensation. A process model of system dynamics is derived. Friction effects are modelled by a neuro-fuzzy Local Linear Model Tree (LOLIMOT) approach. Parameter estimation is obtained with two simple experiments. A friction estimation stage is...
This study proposes a sliding mode control (SMC) framework for the reconstruction and rejection of mismatched and matched unknown disturbances. First, a robust proportional-integral (PI) type controller is designed for dealing with an uncertain scalar system subject to matched disturbance. Then, a 2nd order uncertain system subjected to both matched and mismatched disturbances is discussed. By incorporating...
Macro-Micro bilateral manipulation is a remote control with scaling factor of position/force between master (macro) and slave (micro) system. Normally, bilateral control based on acceleration control can realize not only high performance of force transmission because of the utilization of reaction force observer (RFOB), but also accurate tracking of position because of disturbance observer (DOB)....
This paper makes improvements aiming at the existing problems of hybrid location algorithm combining BS and satellites data and propose the TDOA/DGPS hybrid location algorithm based on the initial estimation. According to simulations with MATLAB, this new algorithm is proved to improve positioning accuracy further and reduce the amount of computation. But this algorithm can not eliminate effect of...
An improved estimation method for a class of nonlinear hybrid systems has been proposed in this paper using a self-switched R-adaptive Extended Kalman Filter. The term ‘estimation of a hybrid system’ implies state estimation as well as mode estimation of a plant. In hybrid systems, where modes are determined by the output variables, the mode determination may become erroneous due to inaccurately known...
An Adaptive Divided Difference filter has been proposed for the systems with non additive Gaussian noise in the situations when noise statistics is unknown. In face of unknown noise statistics the proposed filter can adapt the unknown measurement noise covariance (Ü) incorporating the steps for adaptation in the non adaptive algorithm of Divided Difference filter. Satisfactory estimation performance...
This paper presents a new approach for shortterm load forecasting using the participatory learning paradigm. Participatory learning paradigm is a new training procedure that follows the human learning mechanism adopting an acceptance mechanism to determine which observation is used based upon its compatibility with the current beliefs. Here, participatory learning is used to train a class of hybrid...
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