Search results for "Kalman filter"
showing 10 items of 108 documents
Characterisation of a commercial automotive lithium ion battery using extended Kalman filter
2013
This paper presents a extented Kalman filter based on a dynamic model of a commercial lithium ion battery pack in automotive applications, and experimental data are collected using the Noao. This vehicle is an electric track with range extender, which has been developed and produced by the association Pole de Performance de Nevers Magny-Cours (PPNMC). This model has been developed with MATLAB/Simulink to investigate the output characteristics of lithium-ion batteries. It incorporates I-V performance of the battery, battery capacity fading, temperature effect on battery performance, and the battery temperature rise. This estimation technique is used in order to estimate some parameters, whic…
IWCFTA2012 Keynote Speech I - Hidden attractors in dynamical systems: From hidden oscillation in Hilbert-Kolmogorov, Aizerman and Kalman problems to …
2012
Summary form only given. In this survey an attempt is made to reflect the current trends in the synthesis of analytical and numerical methods to develop efficient analytical-numerical methods, based on harmonic linearization, applied bifurcation theory and numerical methods, for searching hidden oscillations.
Real-time estimation of plasma insulin concentration from continuous glucose monitor measurements
2015
Continuous glucose monitors can measure interstitial glucose concentration in real time for closed-loop glucose control systems, known as artificial pancreas. These control systems use an insulin feedback to maintain plasma glucose concentration within a narrow and safe range, and thus to avoid health complications. As it is not possible to measure plasma insulin concentration in real time, insulin models have been used in literature to estimate them. Nevertheless, the significant interand intra-patient variability of insulin absorption jeopardizes the accuracy of these estimations. In order to reduce these limitations, our objective is to perform a real-time estimation of plasma insulin co…
Analytical-numerical methods for investigation of hidden oscillations in nonlinear control systems
2011
The method of harmonic linearization, numerical methods, and the applied bifurcation the- ory together discover new opportunities for analysis of oscillations of control systems. In the present survey analytical-numerical algorithms for hidden oscillation localization are discussed. Examples of hidden attrac- tor localization in Chua's circuit and counterexamples construction to Aizerman's conjecture and Kalman's conjecture are considered.
Asynchronous sensor fusion of GPS, IMU and CAN-based odometry for heavy-duty vehicles
2021
[EN] In heavy-duty vehicles, multiple signals are available to estimate the vehicle's kinematics, such as Inertial Measurement Unit (IMU), Global Positioning System (GPS) and linear and angular speed readings from wheel tachometers on the internal Controller Area Network (CAN). These signals have different noise variance, bandwidth and sampling rate (being the latter, possibly, irregular). In this paper we present a non-linear sensor fusion algorithm allowing asynchronous sampling and non-causal smoothing. It is applied to achieve accuracy improvements when incorporating odometry measurements from CAN bus to standard GPS+IMU kinematic estimation, as well as the robustness against missing da…
A Kalman Filter Approach for Distinguishing Channel and Collision Errors in IEEE 802.11 Networks
2008
In the last years, several strategies for maximizing the throughput performance of IEEE 802.11 networks have been proposed in literature. Specifically, it has been shown that optimizations are possible both at the medium access control (MAC) layer, and at the physical (PHY) layer. In fact, at the MAC layer, it is possible to minimize the channel waste due to collisions and backoff expiration times, by tuning the minimum contention window as a function of the network congestion level. At the PHY layer, it is possible to improve the transmission robustness, by selecting a suitable modulation/coding scheme as a function of the channel quality perceived by the stations. However, the feasibility…
Tuning of Extended Kalman Filters for Sensorless Motion Control with Induction Motor
2019
This work deals with the tuning of an Extended Kalman Filter for sensorless control of induction motors for electrical traction in automotive. Assuming that the parameters of the induction motor-load model are known, Genetic Algorithms are used for obtaining the system noise covariance matrix, considering the measurement noise covariance matrix equal to the identity matrix. It is shown that only stator currents have to be acquired for reaching this objective, which is easy to accomplish using Hall-effect transducers. In fact, the Genetic Algorithm minimizes, with respect to the system covariance matrix, a suitable measure of the displacement between the stator currents experimentally acquir…
Probabilistic Self-Localization and Mapping - An Asynchronous Multirate Approach
2008
[EN] In this paper, we present a set of robust and efficient algorithms with O(N) cost for the solution of the Simultaneous Localization And Mapping (SLAM) problem of a mobile robot. First, we introduce a novel object detection method, which is mainly based on multiple line fitting method for landmark detection with regular constrained angles. Second, a line-based pose estimation method is proposed, based on LeastSquares (LS). This method performs the matching of lines, providing the global pose estimation under assumption of known Data-Association. Finally, we extend the FastSLAM (FActored Solution To SLAM) algorithm for mobile robot self-localisation and mapping by considering the asynchr…
Dynamic Augmented Kalman Filtering for Human Motion Tracking under Occlusion Using Multiple 3D Sensors
2020
In this paper real-time human motion tracking using multiple 3D sensors has been demonstrated in a relatively large industrial robot work cell. The proposed solution extends state-of-the-art by augmenting the constant velocity model and Kalman filter with low-pass filtered velocity states. The presented method is able to handle occlusions by dynamically inclusion in the Kalman filter of only those 3D sensors which provide valid human position data. Human motion tracking was achieved at a frame rate of 20 Hz, with a typical delay of 50 ms to 100 ms and an estimation accuracy of typically 0.10 m to 0.15 m.
Kalman filter estimation of the contention dynamics in error-prone IEEE 802.11 networks
2008
In the last years, several strategies for maximizing the throughput performance of IEEE 802.11 networks have been proposed in literature. Specifically, it has been shown that optimizations are possible both at the medium access control (MAC) layer, and at the physical (PHY) layer. In fact, at the MAC layer, it is possible to minimize the channel wastes due to collisions and backoff expiration times, by tuning the minimum contention window as a function of the number n of competing stations. At the PHY layer, it is possible to improve the transmission robustness, by selecting a suitable modulation/coding scheme as a function of the channel quality perceived by the stations. However, the feas…