Adaptive filters generally employed for estimation purposes require high computational power when it comes to real time estimation. Therefore, in this paper we propose a computationally light yet effective estimation ...
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ISBN:
(纸本)9781479941667
Adaptive filters generally employed for estimation purposes require high computational power when it comes to real time estimation. Therefore, in this paper we propose a computationally light yet effective estimationalgorithm based on state space model. Our algorithm has been employed successfully in linear and non linear state space model based estimation problems. We investigate few examples to demonstrate the novelty of our algorithm by comparison with few existing algorithms in presence of non Gaussian noise namely uniform noise. More specifically, the state space normalized least mean squares and the Kalman filter has been compared with our algorithm.
Although the weighted least of squares technique is an efficient and well-established power system state-estimation procedure, a number of alternative estimation approaches have been proposed in the technical literatu...
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Although the weighted least of squares technique is an efficient and well-established power system state-estimation procedure, a number of alternative estimation approaches have been proposed in the technical literature. This study presents and compares the most-common estimators formulating them as mathematical programming problems. The numerical accuracy and computational efficiency of the different estimators are analysed using an illustrative case study.
This paper addresses the problem of rigid body orientation tracking. A complementary nonlinear observer is proposed for attitude estimation using inertial/magnetic sensors. The approach developed here is applied in Bi...
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ISBN:
(纸本)9781424453634
This paper addresses the problem of rigid body orientation tracking. A complementary nonlinear observer is proposed for attitude estimation using inertial/magnetic sensors. The approach developed here is applied in Bio-logging, an interdisciplinary research area at the intersection of animal behavior and bioengineering. We propose a state estimation algorithm that combines three complementary data obtained from a 3-axis accelerometer, a 3-axis magnetometer and a 3-axis gyroscope in order to provide the best attitude. The proposed algorithm is based on a nonlinear observer coupled with an Iterated Least Squares algorithm (ISLA). The evaluation of the state estimator by simulation is followed by some experiments illustrating the efficiency of the proposed approach.
Traffic tunnels built in recent years are equipped with traffic counters and pollution sensors. Utilizing these built-in sensors, it is possible to develop an algorithm to estimate the amount of pollutants exhausted f...
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Traffic tunnels built in recent years are equipped with traffic counters and pollution sensors. Utilizing these built-in sensors, it is possible to develop an algorithm to estimate the amount of pollutants exhausted from the various types of vehicles passing through the tunnel. Also, with this estimated data and the sensor outputs, more accurate pollution levels can be assessed utilizing a Kalman filter. The diffusion of pollutants in a tunnel can be described with a one-dimensional diffusion and advection equation. This equation is approximated with interpolation functions and a weighted residual method converts to an adequate form for. standard state estimate algorithms. With this converted equation, a least square based, algorithm is developed, whose outputs are the estimated amounts of pollutants emitted from each type of vehicles. Also, a Kalman filter is utilized to more accurately estimate the pollution levels of the tunnel under the existence of model and measurement uncertainties. In order, to verify the feasibility of the developed algorithms, experiments and simulations are performed. The real data is acquisitioned from the Dunnae tunnel located in Young-Dong highway in Korea. The estimated emission rates and the computer simulated concentration levels agree reasonably to the measured values.
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