Search results for " Kalman"

Fuzzy EKF Control for Wheeled Nonholonomic Vehicles

2006

In this paper a new Fuzzy extended Kalman robust control system for position and orientation tracking of nonholonomic vehicles with two wheels actuated by two independent DC motors is presented. The problem of robustness and localization are solved simultaneously. About the robustness, some perturbations coming from the outside environment and depending on the contact between the wheels and the ground, involve violations of the nonholonomic constraints. The fuzzy controller of this work is able to obtain a dynamic term of robustness with respect to the perturbations above. However, by using encoders only, the measures of actual position and orientation of the vehicle are with Gaussian noise…

Le filtre de Kalman étendu à grand-gain adaptatif et ses applications

2010

The work concerns the “observability problem”—the reconstruction of a dynamic process’s full state from a partially measured state— for nonlinear dynamic systems. The Extended Kalman Filter (EKF) is a widely-used observer for such nonlinear systems. However it suffers from a lack of theoretical justifications and displays poor performance when the estimated state is far from the real state, e.g. due to large perturbations, a poor initial state estimate, etc. . . We propose a solution to these problems, the Adaptive High-Gain (EKF). Observability theory reveals the existence of special representations characterizing nonlinear systems having the observability property. Such representations ar…

Convergence analysis of cubature Kalman filter

2014

This paper investigates the stability analysis of cubature Kalman filter (CKF) for nonlinear systems with linear measurement. The certain conditions to ensure that the estimation error of CKF remains bounded are proved. Then, the effect of process noise covariance is investigated and an adaptive process noise covariance is proposed to deal with large estimation error. Accordingly, a modified CKF (MCKF) is developed to enhance the stability and accuracy of state estimation. The performance of the MCKF is compared to the CKF by two case studies. Simulation results demonstrate that the large estimation error may lead to instability of CKF while the MCKF is successfully able to estimate the sta…

Sustainable Method Using Filtering Techniques for a Fermentation Process State Estimation

2020

Winemaking is concerned about sustainable energy availability that implies new methods for process monitoring and control. The aim of this paper is to realize a comparative analysis of the possibilities offered using estimation techniques, balances, and filtering techniques such as the Kalman filter (KF) and the extended Kalman filter (EKF), to obtain indirect information about the alcoholic fermentation process during winemaking. Thus, an estimation solution of the process variables in the exponential growing phase is proposed, using an extended observer. In addition, two estimation solutions of this process with the EKF and an estimation of the decay phase of the fermentation process are …

Kalman filter tracking and vertexing in a silicon detector for neutrino physics

2002

Abstract This article describes the application of Kalman filter techniques for the tracking and vertexing of particles inside the NOMAD-STAR detector, a silicon vertex detector installed in NOMAD, one of the neutrino oscillation experiments at the CERN-SPS. The use of the Kalman filter simplifies computationally the tracking and vertex procedure for NOMAD-STAR. The alignment of NOMAD-STAR is shown as an example of the application of the Kalman filter for tracking purposes. The accuracy of the method is such that one obtains alignment residuals between 9 and 12 μm . Furthermore, a preliminary measure of the impact parameter (with an RMS ∼36 μm ) illustrates the vertexing capabilities of thi…

Invariant pattern recognition based on 1-D Wavelet functions and the polynomial decomposition

1997

Abstract A new filter, consisting of 1-D Wavelet functions is suggested for achieving optical invariant pattern recognition. The formed filter is actually a real function, hence, it is theoretically possible to be implemented under both spatially coherent and spatially incoherent illuminations. The filter is based on the polynomial expansion, and is constructed out of a scaled bank of filters multiplied by 1-D Wavelet weight functions. The obtained output is shown to be invariant to 2-D scaling even when different scaling factors are applied on the different axes. The computer simulations and the experimental results demonstrate the potential hidden in this technique.

Sensorless Control of Induction-Motor Drive Based on Robust Kalman Filter and Adaptive Speed Estimation

2014

This paper deals with robust estimation of rotor flux and speed for sensorless control of motion control systems with an induction motor. Instead of using sixth-order extended Kalman filters (EKFs), rotor flux is estimated by means of a fourth-order descriptor-type robust KF, which explicitly takes into account motor parameter uncertainties, whereas the speed is estimated using a recursive least squares algorithm starting from the knowledge of the rotor flux itself. It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates. E…

AN EKF BASED PROCEDURE FOR AUTOMATIC PATH FOLLOWING IN TURBULENT AIR

2017

Aim of the present paper is to propose a procedure to afford an accurate automatic path following in turbulent air. The technique is based on the simultaneous employment of two different EKF. The first estimates disturbances, the second one estimates deflection that are necessary to reject the estimated disturbances. The first EKF uses measurements gathered in turbulent air. The second EKF obtains command laws able to follow the desired flight path rejecting disturbances. To purchase the objective, aerodynamic coefficients have been modified by adding entirely new derivatives or synthetic increments to basic ones. The modified aircraft parameters are determined by augmenting the aircraft’s …

Estimation of turbulence and state based on EKF for a tandem Canard UAV

2008

This paper deals with the state and turbulence estimation of a model describing the longitudinal dynamics of an Unmanned Aerial Vehicle (UAV). Due to both the high nonlinearities of the model and the stochastic nature of disturbances, an Extended Kalman Filter (EKF) is proposed. To allow the estimator to be employed on low cost UAV systems, it is assumed that the aircraft is equipped with a low performance GPS, characterized by a relatively low refresh rate. The designed EKF is able to work efficiently in both turbulent and calm atmosphere. In order to obtain information about the performances of the proposed estimator for control purposes, a control system, consisting of the EKF, a PID-typ…

Advanced Motion Control in Induction Motor Systems - Modelling, Analysis and Control

Using a unified notation, this thesis collects and discusses the most important steps and issues in the design of estimation and control algorithms for induction motors. It contains many estimation and control algorithms. Their stability is analyzed and their performance is illustrated by simulations and experiments on the same induction motor. An intense and challenging collective research effort is carefully documented and analyzed, with the aim of providing and clarifying the basic intuition and tools required in the analysis and design of nonlinear feedback control algorithms. This material should be of specific interest to engineers who are engaged in the design of control algorithms f…