Robust control problems for nonlinear systems are usually formulated as L2-induced norm minimization problems and it is known that those problems are reduced to the solvability of Hamilton-Jacobi equations. However, i...
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A sixteen-channel linear phased array radar is calibrated by means of Artificial Neural Network (ANN). Limited data are used to train the various layers of the network, for Angle of Arrival (AOA) determinacy. This is ...
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ISBN:
(纸本)9781457710407
A sixteen-channel linear phased array radar is calibrated by means of Artificial Neural Network (ANN). Limited data are used to train the various layers of the network, for Angle of Arrival (AOA) determinacy. This is designed to increase speed of operation and to prevent over fitting. The designed simulator generates time-series data sets representing continuous span of AOA. The generated data-sets are used in multilayer feed-forward NNs to find the phase, which is then used as inputs to Spiking Neural Network (SNN) o determine AOA. SNNs are used for hardware implementation feasibility. The designed simulator improved the accuracy of AOA determination, and opens the door for a wide variety of radar classification applications.
A problem of assessing stability of retarded dynamical networks is solved in this paper. Subsystems are assumed to be integral input-to-state stable (iISS). Time-delays are allowed to reside in both subsystems and int...
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We create a spiking neural network of Integrate and Fire neurons with spike frequency adaption based on parameters adjusted for our e-nose device, and investigate the use of this model for odor classification. Additio...
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ISBN:
(纸本)9781457710407
We create a spiking neural network of Integrate and Fire neurons with spike frequency adaption based on parameters adjusted for our e-nose device, and investigate the use of this model for odor classification. Addition of spike frequency adaptation term brings the model closer to the response of the olfactory system. Data from Cyranose 320, a polymer based 32-sensor array, is used to test the system and create unique dynamic spiking patterns. The results for four analytes are presented.
This paper gives a solution to the problem of verifying stability of networks consisting of integral input-to-state stable (iISS) subsystems. The iISS small-gain theorem developed recently has been restricted to inter...
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Abstract This paper describes the development of an active vibration control system for a light and flexible stress ribbon footbridge. The 13 m span Carbon Fiber Reinforced Plastics (CFRP) stress ribbon bridge was bui...
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Abstract This paper describes the development of an active vibration control system for a light and flexible stress ribbon footbridge. The 13 m span Carbon Fiber Reinforced Plastics (CFRP) stress ribbon bridge was built in the laboratory of the Department of Civil and Structural engineering, Berlin Institute of Technology. Its lightness and flexibility result in high vibration sensitivity. To reduce pedestrian-induced vibrations, very light pneumatic muscle actuators are placed at handrail level introducing control forces. First, a reduced discretized analytical model is derived for the stress ribbon bridge. To verify the analytical prediction, experiments without feedback control are conducted. Based on this model, a velocity feedback control strategy is designed to actively control first mode vibrations. To handle the nonlinearities of the muscle actuator a subsidiary nonlinear force controller is implemented based on exact linearisation methods. The stability of the entire closed-loop system with actuator saturation is investigated by the Popov Criterion. Control performance is verified by experiments. It is demonstrated that handrail introduced forces can efficiently control the first mode response.
This paper presents a novel tracker, based on combining a linear chain conditional random field (CRF) adaptive multi-resolution segmentation with an unscented Kalman filter (UKF). Specifically, the proposed method com...
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This paper presents a novel tracker, based on combining a linear chain conditional random field (CRF) adaptive multi-resolution segmentation with an unscented Kalman filter (UKF). Specifically, the proposed method combines multiple features and multiple resolutions to facilitate video tracking. The advantages of our method lie in its speed and robustness. Speed is dramatically improved by taking into account multiple resolutions in one dimensional CRF-based segmentation. Robustness is achieved by using multiple cues. The performance of the proposed method is demonstrated in human head tracking with a non-stationary camera. Results show that we are able to maintain real-time processing on quite generous video sequences. The paper argues that our approach is faster, more efficient and more robust than the conventional UKF.
Plug-in hybrid electric vehicles (PHEVs) play an important role in making a greener future. Given a group of PHEVs distributed across a power network equipped with the smart grid technology (e.g. wireless communicatio...
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ISBN:
(纸本)9781457710001
Plug-in hybrid electric vehicles (PHEVs) play an important role in making a greener future. Given a group of PHEVs distributed across a power network equipped with the smart grid technology (e.g. wireless communication devices), the objective of this paper is to study how to schedule the charging of the PHEV batteries. To this end, we assume that each battery must be fully charged by a pre-specified time, and that the charging rate can be time-varying at discrete-time instants. The scheduling problem for the PHEV charging can be augmented into the optimal power flow (OPF) problem to obtain a joint OPF-charging (dynamic) optimization. A solution to this highly nonconvex problem optimizes the network performance by minimizing the generation and charging costs while satisfying the network, physical and inelastic-load constraints. A global optimum to the joint OPF-charging optimization can be found efficiently in polynomial time by solving its convex dual problem whenever the duality gap is zero for the joint OPF-charging problem. It is shown in a recent work that the duality gap is expected to be zero for the classical OPF problem. We build on this result and prove that the duality gap is zero for the joint OPF-charging optimization if it is zero for the classical OPF problem. The results of this work are applied to the IEEE 14 bus system.
In this paper, we investigate the performance of a single relay assisted cooperative vehicular network in a highway traffic scenario. Source and relaying vehicles are assumed to be traveling in the same direction with...
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In this paper, we investigate the performance of a single relay assisted cooperative vehicular network in a highway traffic scenario. Source and relaying vehicles are assumed to be traveling in the same direction with similar speeds. This results in a relative velocity nearly equal to zero and leads to a frequency-flat and time-flat fading in source-to relay link. On the other hand, source-to-destination and relay to-destination links are modeled as doubly-selective fading. To handle spreading in time and frequency, we propose a precoded cooperative scheme to exploit delay and Doppler spreads to our advantage. Under the assumption of amplify-and-forward relaying with orthogonal cooperation protocol, we derive a pairwise error probability expression and demonstrate the achievable diversity gains. We further conduct Monte Carlo simulations to confirm the analytical derivations and present the error rate performance of the proposed scheme with imperfect channel estimation.
The paper focuses on the problem of structure from motion and proposes a spatial-and-temporal-weighted factorization algorithm. The contributions of the paper are as follows: First, it is demonstrated that the image r...
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The paper focuses on the problem of structure from motion and proposes a spatial-and-temporal-weighted factorization algorithm. The contributions of the paper are as follows: First, it is demonstrated that the image reprojection error is generally in proportion to the error magnitude contained in the image. Second, the error distribution contained in the measurement matrix is modelled spatially and temporally from the image reprojection residuals. Third, based on the estimated error distribution, a spatial-and-temporal-weighted factorization algorithm is proposed to handle the uncertainty caused by significant image noises. Compared with existing approaches, the proposed technique does not require a prior information of image measurement, and it is easy to implement. Extensive experiments on synthetic data and real images are performed to validate the proposed method.
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