Search results for "Extended Kalman Filter"
showing 10 items of 44 documents
Automatic EKF tuning for UAS path following in turbulent air
2018
By using two simultaneously working Extended Kalman Filters, a procedure is implemented in order to perform in a fully autonomous way the path following in turbulent air. To guarantee the robustness of the proposed algorithm, an automatic tuning procedure is proposed to determine optimal values of Process and Measurement Noise statistics. Such a procedure is based on both the characteristics of the disturbances and the desired flight path; in particular, a specific performance index is applied to tune filters. In this way control laws are adapted to the flight condition and these lead to an optimal path-following. This research represents an upload of previous papers. It allows eliminating …
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…
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 …
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.
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…
State Estimation of a Nonlinear Unmanned Aerial Vehicle Model using an Extended Kalman Filter
2008
An Extended Kalman Filter is designed in order to estimate both state variables and wind velocity vector at the same time for a non conventional unmanned aircraft. The proposed observer uses few measurements, obtained by means of either conventional simple air data sensors or a low cost GPS. To cope with the low rate of the GPS with respect to the other sensors, the EKF algorithm has been modified to allow for a dual rate measurement model. State propagation is obtained by means of an accurate six degrees of freedom nonlinear model of the aircraft dynamics. To obtain joint estimation of state and disturbance, wind velocity components are included in the set of the state variables. Both stoc…
Extended Kalman Filter for sensorless control of induction motors
2010
This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the design…
Supercapacitor diagnosis using an Extended Kalman Filtering approach
2016
This paper deals with the model-based analysis of a Supercapacitor for diagnostic purposes. A two legs nonlinear physical model is assumed for the Supercapacitor and the corresponding second-order nonlinear state-space mathematical model is obtained. Then, an Extended Kalman Filter is tuned so that the estimated outputs reproduce the voltages at the equivalent capacitance terminals; they give information on the state of health of the supercapacitor but are not directly measurable. In particular, an optimization problem is firstly formulated, involving the experimental input-output data and those given by the Extended Kalman Filter.