A novel modeling method of T-S fuzzy system for an affine nonlinear system is proposed. Based on this method, the responses of T-S fuzzy system is the same as the original nonlinear, the modeling error is avoided comp...
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A novel modeling method of T-S fuzzy system for an affine nonlinear system is proposed. Based on this method, the responses of T-S fuzzy system is the same as the original nonlinear, the modeling error is avoided compared with the linearization method around the equilibrium points, and this method can be applied the nonlinear system contained the multiple nonlinear terms. T-S fuzzy model of GMAW system is established, the response characteristics of the T-S fuzzy system are not changed compared with the nonlinear GMAW system. The simulation result proves the validity of this method.
A conceptual map model of environments is proposed for task planning of service robots in semantic knowledge space. Such model is characterized with a layered structure containing ontology, spatial and user knowledge....
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A conceptual map model of environments is proposed for task planning of service robots in semantic knowledge space. Such model is characterized with a layered structure containing ontology, spatial and user knowledge. It is capable of inferring environmental knowledge and mapping semantic plans onto the instantial perception space. A scene recognition based method for conceptual map building and updating is proposed to support the environment learning capabilities of robots. Using such model, a layered topological and metric navigation strategy is proposed, in which map switching technique ensures that Monte Carlo localization and metric path planning are performed within each small-scale grid map. Experimental results in large-scale office environments validate the effectiveness and efficiency of robot localization and navigation, and a semantic navigation manner is achieved.
A class of complex hybrid time-delay models for network controlsystems have been constructed by taking the characteristics of network into account. Based on a LMI(linear matrix inequality) method, a kind of Lyapunov-...
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A class of complex hybrid time-delay models for network controlsystems have been constructed by taking the characteristics of network into account. Based on a LMI(linear matrix inequality) method, a kind of Lyapunov-Krasovskii functional is employed, and the controller design is discussed for this type of systems. As input control is in discrete-time and the input delay constant is known, while state is in continuous-time and the state delay constant is not known exactly, so the system is constructed based on two models in both continuous-time domain and discrete-time domain. At the same time, a new type of adaptive control strategy for the unknown delay parameter is proposed in this paper, which realizes that the unknown delay parameter can always be reflected in the memory state-feedback controller. Delay-dependent sufficient conditions for the existence of the feedback controller in terms of LMIS are obtained.
The classical mean shift tracking algorithm is apt to make errors or lose the target if the target is occluded for a very long time. Thus an improved mean shift tracking algorithm is proposed. This algorithm divides t...
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The classical mean shift tracking algorithm is apt to make errors or lose the target if the target is occluded for a very long time. Thus an improved mean shift tracking algorithm is proposed. This algorithm divides the target into multiple fragments and integrates spatial information by using different weights of each image fragment. The similarity coefficient between target template and candidate template consists of the Bhattacharyya coefficients of the corresponding multiple fragments. Experimental results show that the proposed method is efficient when the target is occluded for a long time. A new method named edge-histogram is used. This method is based on original scale updating mechanism and make a further judgment that whether the target is smaller or not by calculating the Bhattacharyya coefficient between the target's edge-histograms of the current frame and the previous one. Experimental results show that the proposed algorithm can deal with the scale problem very well.
In order to solve the problems of inaccurate positioning in current vehicle monitoring systems, an intelligent vehicle monitoring system based on mobile video and WebGIS (Web geographic information system) is proposed...
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In order to solve the problems of inaccurate positioning in current vehicle monitoring systems, an intelligent vehicle monitoring system based on mobile video and WebGIS (Web geographic information system) is proposed and designed. The system is composed of front-end equipment, system platform and client. The instant image information captured by vehicle mobile video and the GPS(global positioning system) positioning location information received by the terminal are transmitted from front-end to system platform via the GPRS(general packet radio service) mobile communications platform. Also, a highly compressed digital video and audio codec technology standard named H.264/AVC is employed to compress the real-time mobile video information and the Google Maps API is called to display the current position of vehicles on the electronic map. Furthermore, the spatial analysis capabilities of GIS plus the GPS information not only make tracking feasibly, but also provide aid in decision making. It is shown that the system can not only reproduce the video data timely and accurately, but also accurately position the mobile vehicles so as to provide a better service in monitoring, control, management, analysis, decision-making and command functions, which expands the application fields and development prospects of WebGIS and mobile video monitoring technology.
In order to achieve the goal of data statistic and task management under the embedded systems, together with the consideration of processing speed and the internal storage capacity, the embedded database is introduced...
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In order to achieve the goal of data statistic and task management under the embedded systems, together with the consideration of processing speed and the internal storage capacity, the embedded database is introduced. The features of embedded database are small in size, multi-functional, portable, highly efficient and stable. Taking the data management in the home energy monitor system as an example, a statistical method of time sharing is proposed. The embedded database Berkeley DB is transplanted, and the resource occupancy and response speed before and after using Berkeley DB are compared. Testing data show that although taking up more storage resources, the use of Berkeley DB provides more efficient data management capabilities. The application of Berkeley DB improves the system response, and provides a better human-computer interaction. Under the allowance of the hardware resources of device, this practice of using space for performance is feasible.
When it comes to the issue of path planning for mobile service robots in structured indoor environments, traditional A* algorithm fails to display a good performance of real-time path tracking. Therefore, a new method...
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When it comes to the issue of path planning for mobile service robots in structured indoor environments, traditional A* algorithm fails to display a good performance of real-time path tracking. Therefore, a new method is proposed to design a near-optimal smooth path. Mobile robots can thus track the path smoothly and reach the goal fast. At first, the improved A* algorithm is applied to plan a proper trajectory for the mobile robot. Then a key-point optimization process is applied to make the global path simplified to be connections among a series of key points. The most important improvement lies in the introduction of the polar polynomials curve to smooth the path according to the constraints of position, curvature and slope. However, when the arc turns become 90° or more, the optimized piecewise-polynomial-function curve is generated to replace the original one. Experimental results prove that the path generated meets the dynamic characteristics of the mobile robots as well as the geometric features. The requirements of quick real-time computation of path tracking process can be well satisfied.
A new phase-shifting error compensating algorithm for phase-measuring profilometry is proposed. In this error detecting algorithm, it is supposed that sinusoidal fringe is projected to the plate, thus the phase differ...
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A new phase-shifting error compensating algorithm for phase-measuring profilometry is proposed. In this error detecting algorithm, it is supposed that sinusoidal fringe is projected to the plate, thus the phase differences between adjacent pixels are equal. Three adjacent phase points are taken as the research object. Combining the principle of phase compensation measurement, each phase of the point is presented as an equation containing the phase-shifting error. According to the characteristics that the phase differences between adjacent pixels are equal, an equation to calculate the phase-shifting error is constructed. Then the phase shifting error is taken into account in the original algorithm for error compensation. Simulation results show the inhibitory effect of the error compensation by using the novel algorithm. The proposed algorithm is also used for three-dimensional reconstruction. The final result shows that the new compensation algorithm is better than the original one obviously. This error compensating algorithm can effectively improve the accuracy of three-dimensional measurement.
Malaria is one of the most serious parasitic infections of human. The accurate and timely diagnosis of malaria infection is essential to control and cure the disease. Some image processing algorithms to automate the d...
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Malaria is one of the most serious parasitic infections of human. The accurate and timely diagnosis of malaria infection is essential to control and cure the disease. Some image processing algorithms to automate the diagnosis of malaria on thin blood smears are developed, but the percentage of parasitaemia is often not as precise as manual count. One reason resulting in this error is ignoring the cells at the borders of images. In order to solve this problem, a kind of diagnosis scheme within large field of view (FOV) is proposed. It includes three steps. The first step is image mosaicing to obtain large FOV based on space-time manifolds. The second step is the segmentation of erythrocytes where an improved Hough Transform is used. The third step is the detection of nucleated components. At last, it is concluded that the counting accuracy of malaria infection within large FOV is finer than several regular FOVs.
In order to describe precisely the dynamics and friction nonlinearity of servo systems, a novel direct identification method for nonlinear continuous model is proposed. The sampled input-output data and logic data cor...
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In order to describe precisely the dynamics and friction nonlinearity of servo systems, a novel direct identification method for nonlinear continuous model is proposed. The sampled input-output data and logic data corresponding to the velocity direction are chosen as the identification data. Through equivalent transformation, the unknown parameters are removed to the linear part of the model. Then the identification method based on state variable filter is utilized to determine the unknown parameters. Subsequently, the nonlinear continuous model of the servo system is obtained. The effectiveness of the proposed method is demonstrated by simulations and identification experiments on the two axis servo table. Both the simulations and experimental results show that, with the proposed method, the accurate nonlinear continuous model can be obtained even under sensor noises, which gives an accurate description of the system dynamics.
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