作者：
王魏李柠李少远Department of Automation
Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China
This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV ar...
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This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV array. The relationship of PV cell and PV array is obtained and the solution for PV array model is unique. The PV grid-connected generation system is used to demonstrate the effectiveness of the proposed method by comparing the calculated values with the actual output of the system.
The stability of quantized innovations Kalman filtering (QIKF) is analyzed. In the analysis, the correlation between quantization errors and measurement noises is considered. By taking the quantization errors as a ran...
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The stability of quantized innovations Kalman filtering (QIKF) is analyzed. In the analysis, the correlation between quantization errors and measurement noises is considered. By taking the quantization errors as a random perturbation in the observation system, the QIKF for the original system is equivalent to a Kalman-like filtering for the equivalent state-observation system. Thus, the estimate error covariance matrix of QIKF can be more exactly analyzed. The boundedness of the estimate error covariance matrix of QIKF is obtained under some weak conditions. The design of the number of quantized levels is discussed to guarantee the stability of QIKF. To overcome the instability and divergence of QIKF when the number of quantization levels is small, we propose a Kalman filter using scaling quantized innovations. Numerical simulations show the validity of the theorems and algorithms.
An accuracy assessment method that integrates segmentation and classification accuracy is proposed to meet the requirements of object-based image analysis. Segmentation errors are measured by establishing the relation...
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This paper proposes a particle swarm optimization（PSO） based particle filter（PF） tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state t...
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This paper proposes a particle swarm optimization（PSO） based particle filter（PF） tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state transition stage,and simultaneously incorporates the newest observations into the proposal distribution in the update *** the proposed approach,likelihood measure functions involving multiple features are presented to enhance the performance of model ***,the multi-feature weights are self-adaptively adjusted by a PSO algorithm throughout the tracking *** are three main ***,the PSO algorithm is fused into the PF framework,which can efficiently alleviate the particles degeneracy ***,an effective convergence criterion for the PSO algorithm is explored,which can avoid particles getting stuck in local minima and maintain a greater particle ***,a multi-feature weight self-adjusting strategy is proposed,which can significantly improve the tracking robustness and *** performed on several challenging public video sequences demonstrate that the proposed tracking approach achieves a considerable performance.
Synchronization and pinning control of complex networks is to regulate the agents' behavior and improve network performance. In this article, we review some recent developments in pinning control. Stability algori...
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Soft-sensing is widely used in industrial applications. The traditional soft-sensing structure is open-loop without correction mechanism. If the working condition is changed or there is unknown disturbance, the foreca...
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Soft-sensing is widely used in industrial applications. The traditional soft-sensing structure is open-loop without correction mechanism. If the working condition is changed or there is unknown disturbance, the forecast result of soft-sensing model may be incorrect. In order to obtain accurate values, it is necessary to carry out online correction. In this paper, a semiclosed-loop framework (SLF) is proposed to establish a soft-sensing approach, which estimates the input variables in the next moment by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and robustness than other open-loop models.
An algorithm is presented for computing the reachable set of a dynamic system. The algorithm is based on a proof that the reachable set is the zero sublevel set of the viscosity solution of a particular time-dependent...
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ISBN:
(纸本)9781849196413
An algorithm is presented for computing the reachable set of a dynamic system. The algorithm is based on a proof that the reachable set is the zero sublevel set of the viscosity solution of a particular time-dependent Hamilton-Jacobi-Isaacs partial differential equation (HJI PDE). We implement this approach to a more realistic aircraft dynamic model which the control input of this model can be given by pilot rather than general intermediate variables. According to desired trajectory states, we can compute the backward reachable set in certain time interval and use the simulate result to verify actual trajectory status.
A radar ECCM method is proposed to combat the repeat jamming. Benfitting from the full-rate orthogonal pulse block design of such method, all the received signals within a pulse block are employed in the match filteri...
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ISBN:
(纸本)9781849196765
A radar ECCM method is proposed to combat the repeat jamming. Benfitting from the full-rate orthogonal pulse block design of such method, all the received signals within a pulse block are employed in the match filtering operation for false target cancellation, which improves the SNR of real targets. And the Two-dimensional frequency domain motion compensation automatically removes the impact of target motion on canceling out multiple false targets with different and unknown motion parameters. The numerical examples demonstrate the effectiveness of the proposed method.
In this paper, we present a method for object detection and localization using the technique of random forest. In the process of supervised learning to construct random forest, we use the descriptor vectors of the SIF...
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The overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive met...
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