In the time domain, on the basis of two-probe straightness error separation technology, this paper gives a new measurement measuring the flatness error based on the error separation technology-the two-probe flatness e...
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ISBN:
(纸本)1424435064
In the time domain, on the basis of two-probe straightness error separation technology, this paper gives a new measurement measuring the flatness error based on the error separation technology-the two-probe flatness error separation measurement. It also gives the principle of the two-probe flatness error separation measurement, establishes the corresponding mathematical models, and carries on the simulation analysis and experiment testifying. Theoretical simulation and experimental result have proved the correctness and effectiveness of the separation principle (1) after analyzing the data with the two-probe error separation measurement, we can obtain the flatness of the panel measured as well as the straight error of the guiding rail.(2) when measuring with the two-probe measurement, the accumulation error of the initial position of the sensors is linear, so it can not influent the assessment of the error.(3) the two-probe error separation technology uses less one or two probes than the flatness error separation technology with the three or four probes does, so it need not consider installing several sensors on a plane and eliminates the problem made by the non-linear accumulation error of the initial position of the sensors. Therefore, the two-probe flatness error separation measurement this paper gives can make the flatness error separation technology more applied.
This study presents an effective system for detecting and tracking moving vehicles in nighttime traffic scene for traffic surveillance. The proposed method identifies vehicles based on detecting and locating vehicle h...
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This work presents a strategy to track and describe the boundary of an environmental surface using a sequence of incomplete boundary images coming from an UAV with a camera onboard. The algorithm uses all captured ima...
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This work presents a strategy to track and describe the boundary of an environmental surface using a sequence of incomplete boundary images coming from an UAV with a camera onboard. The algorithm uses all captured images to feed the trajectory, which drives the UAV towards the next point to take the next shot, until the identification is completed. The multiple patterns of the input image make the problem difficult. Our approach orders the points of the image to identify the existent edges, and computes the trajectory as a minimization problem using a multi-objective function that gathers information about the boundary and the polynomial that fit in these edges.
Techniques for optimal control of hybrid systems have to consider the complex interaction of continuous and discrete dynamics and are required to limit the computational complexity arising from the corresponding searc...
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ISBN:
(纸本)9783902661593
Techniques for optimal control of hybrid systems have to consider the complex interaction of continuous and discrete dynamics and are required to limit the computational complexity arising from the corresponding search spaces. This contribution proposes an approach to computing hybrid optimal control trajectories based on an iterative model-abstraction and refinement scheme. The hybrid automaton is mapped to an abstract representation which is enriched by cost information gained from graph. Candidate solutions are computed on the abstract level and are mapped back to the level of the hybrid model, where they are validated. A refinement step guides the search for (sub-) optimal hybrid control trajectories. The proposed approach is implemented for the optimization of the start-up procedure for a chemical reactor.
In contemporary society, access to information is easy because of advanced communication media, so security system which prevent unauthorized access is considered important. Fingerprint verification systems are very c...
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In this paper, we propose the novel emotional engine like human's emotion and its parameter tuning using by hybrid system bacterial foraging (BF) and agent machine learning. The most general method uses neural net...
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ISBN:
(纸本)9781424444779
In this paper, we propose the novel emotional engine like human's emotion and its parameter tuning using by hybrid system bacterial foraging (BF) and agent machine learning. The most general method uses neural networks to classify emotion by using speech and face image data for human's emotion recognition. But high-dimension and large size of this data cause low-speed learning of neural network. The main idea of the proposed method is to suggest emotion engine and to express emotion by hybrid system composed of bacterial foraging and multi-agent system. Experimental result shows that this method can achieve better performance for human's emotion recognition than others and express emotion.
Protocol testing has been one of the most active fields in computer networks. In Wireless Sensor Networks (WSNs),before directly employing protocols on hardware testbed, we expect an effective test framework to verify...
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Scale-free network and consensus among multiple agents have both drawn quite much attention. To investigate the consensus speed over scale-free networks is the main topic in this paper. Given a set of different values...
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Scale-free network and consensus among multiple agents have both drawn quite much attention. To investigate the consensus speed over scale-free networks is the main topic in this paper. Given a set of different values for the power-law distribution parameter γ, and a set of different values for the minimum degree ( d min ) for the nodes, the algebraic connectivity (λ 2 ) of the network topology is studied, as well as the time ( t c ) (or iteration ( k c ), for discrete algorithm) taken to reach consensus. The results exhibit that λ 2 decreases while γ increases. The λ 2 increases monotonically as d min grows, and they fit very well in a linear relationship. t c (or k c ) decreases as γ reduces and d min increases. Via observing the behavior of the largest eigenvalue (λ n ) of the Laplacian of the network topology, we draw the conclusion that the robustness over time delays declines while the robustness over node-failures and edge-failures increases.
The paper presents a methodology for feedback adaptive control of active vibration systems in the presence of time varying unknown multiple narrow band disturbances. A direct adaptive control scheme based on the inter...
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The paper presents a methodology for feedback adaptive control of active vibration systems in the presence of time varying unknown multiple narrow band disturbances. A direct adaptive control scheme based on the internal model principle and the use of the Youla-Kucera parametrization is proposed. This approach is comparatively evaluated with respect to an indirect adaptive control scheme based on the estimation of the disturbance model. The evaluation of the methodology is done in real time on an active suspension system and on an active vibration control system using an inertial actuator.
This paper is concerned with system level energy management in wireless sensor networks. The network is required to conduct certain tasks which require information from individual sensors to be sent to a base station....
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This paper is concerned with system level energy management in wireless sensor networks. The network is required to conduct certain tasks which require information from individual sensors to be sent to a base station. Sensors cease functioning when they deplete their energy reserves or may fail abruptly due to random malfunctions. Sensor selection refers to the number of times sensors are interrogated, while sensor scheduling refers to the sequence in which these interrogations are conducted. A sensor management layer that isolates the system objectives from selection/scheduling is proposed. It is shown that sensor selection reduces to integer linear programming. Sensor scheduling is necessary when random sensor failures are considered or when the task definition is not stationary. Some general principles emerge. If all sensors are equally reliable, the optimal policy is to use the most energetic sensors first. If all sensors are equally energetic, the optimal policy is to use the least reliable sensor first.
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