This paper provides a novel estimation procedure for determining the number of high-dimensional complex-valued signals embedded in Gaussian white noise. Initially, this problem is formulated as a sequence of nested hy...
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Considering the Conservative Power Theory (CPT), this paper proposes some novel compensation strategies for shunt passive or active devices. The CPT current decompositions result in several current terms, which are as...
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ISBN:
(纸本)9781424454365;9781424454358
Considering the Conservative Power Theory (CPT), this paper proposes some novel compensation strategies for shunt passive or active devices. The CPT current decompositions result in several current terms, which are associated with specific physical phenomena (average power consumption P, energy storage Q, load and source distortion D, unbalances N). These current components were used in this work for the definition of different current compensators, which can be selective in terms of minimizing particular disturbing effects. Compensation strategies for single and three-phase four-wire circuits have also been considered. Simulation results have been demonstrated in order to validate the possibilities and performance of the proposed strategies.
This paper presents an intelligent method for analyzing differences in the electricity industry standards by utilizing natural language processing. The main goal of this approach is to detect variations between standa...
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The cutoff frequency of a LC output filter for dynamic voltage restorers (DVR) limits the control bandwidth of a DVR system and the attenuation factor against the inverter switching ripples. For a selected cutoff freq...
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ISBN:
(纸本)0780383990
The cutoff frequency of a LC output filter for dynamic voltage restorers (DVR) limits the control bandwidth of a DVR system and the attenuation factor against the inverter switching ripples. For a selected cutoff frequency of a LC output filter, infinite number of L-C combinations is possible. Although different L-C combination has different filter characteristics, the filter design on L-C combination has been depended on field experiences without clear analysis. This paper proposes a design criterion and a design example for the L-C filter combination considering the control characteristics and the size of DVRs. An experimental DVR system based on the proposed LC output filter design methodology is built and tested.
Nowadays having the most energy efficiency is desirable in its own right from both economical and environmental points of view. Dynamic power management is a system level solution for reducing the consumed energy with...
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Nowadays having the most energy efficiency is desirable in its own right from both economical and environmental points of view. Dynamic power management is a system level solution for reducing the consumed energy with putting off unused parts of the system and putting them on in an efficient time. The Emotional Learning Algorithm has been introduced to show the effect of emotions as well known stimuli in the quick and almost satisfying decision making in human. The remarkable properties of emotional learning, low computational complexity and fast training, and its simplicity in multi objective problems has made it a powerful methodology in real time control and decision systems, where the gradient based methods and evolutionary algorithms are hard to be used due to their high computational complexity. Recently the emotional approach has been successfully used to obtain multiple objectives in prediction problems of real world phenomena. At first we introduce methods of dynamic power management and then a new method based on BELBIC would be explained. The simulation results show that this method has a high efficiency in various systems.
Ant colony optimization (ACO) is a population-based meta-heuristic for combinatorial optimization problems such as communication network routing problem (CNRP). This paper proposes an improved ant colony optimization ...
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Ant colony optimization (ACO) is a population-based meta-heuristic for combinatorial optimization problems such as communication network routing problem (CNRP). This paper proposes an improved ant colony optimization (IACO), which adapts a new strategy to update the increased pheromone, called ant-weight strategy, and a mutation operation, to solve CNRP. The simulation result for a benchmark problem is reported and compared to the simple ant colony optimization (ACO).
With the development of technology and sustainable concept, ground source heat pump has gradually emerged in the heating industry, which is a new heating technology with the advantages of clean and high efficiency. Ho...
With the development of technology and sustainable concept, ground source heat pump has gradually emerged in the heating industry, which is a new heating technology with the advantages of clean and high efficiency. However, with the continuous operation of the heat pump system, various faults may occur in the internal equipment of the system, such as evaporator fouling, compressor leakage, refrigerant line blockage, etc. It is of great practical significance to identify the fault types accurately and effectively. In this paper, the signal processing method adopts the ensemble empirical mode decomposition, which decomposes the collected ground source heat pump system signals, retains the relevant modal parameters and removes the residual terms, then evaluates each modal component using the approximate entropy as the feature evaluation index, and clusters the entropy values into feature vectors to determine the fault types. The experimental results show that the algorithm based on the combination of ensemble empirical mode decomposition and clustering can be applied to the fault diagnosis accuracy of ground source heat pump systems.
Belief propagation (BP) is a well-celebrated iterative optimization algorithm in statistical learning over network graphs with vast applications in many scientific and engineering fields. This paper studies a fundamen...
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ISBN:
(纸本)9781479978878
Belief propagation (BP) is a well-celebrated iterative optimization algorithm in statistical learning over network graphs with vast applications in many scientific and engineering fields. This paper studies a fundamental property of this algorithm, namely, its convergence behaviour. Our study is conducted through the problem of distributed state estimation for a networked linear system with additive Gaussian noises, using the weighted least-squares criterion. The corresponding BP algorithm is known as Gaussian BP. Our main contribution is to show that Gaussian BP is guaranteed to converge, under a mild regularity condition. Our result significantly generalizes previous known results on BP's convergence properties, as our study allows general network graphs with cycles and network nodes with random vectors. This result is expected to inspire further investigation of BP and wider applications of BP in distributed estimation and control.
To address the formation tracking issue of mobile robotic systems, this paper constructs a novel hybrid dynamic event-triggered intermittent control strategy, which can achieve the exponential synchronization of the s...
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To address the formation tracking issue of mobile robotic systems, this paper constructs a novel hybrid dynamic event-triggered intermittent control strategy, which can achieve the exponential synchronization of the systems. Considering the limited control resources, the intermittent control method is introduced into the distributed control strategy to save resources, and the existing intermittent control model is reconstructed to describe the system model better. A hybrid dynamic event-triggered mechanism is developed by combining the dynamic event-triggered method with the time sampling strategy, eliminating the Zeno phenomenon. The control time sequences in the developed intermittent control strategy are automatically selected by the hybrid dynamic event-triggered sequences, rather than artificially designed in advance, which reduces a certain degree of design complexity. The developed control strategy effectively saves control resources while alleviating the burden of network communication. Sufficient conditions for achieving exponential synchronization formation tracking are provided, and the exponential convergence of the formation error is demonstrated through the proposed lemma. Finally, a control task of multi-mobile robots formation is presented to verify the effectiveness of the theoretical analysis. IEEE
Recently, many researchers have demonstrated that computation by DNA tile self-assembly may be scalable and it is considered as a promising technique in nanotechnology. In this paper, we show how the tile self-assembl...
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Recently, many researchers have demonstrated that computation by DNA tile self-assembly may be scalable and it is considered as a promising technique in nanotechnology. In this paper, we show how the tile self-assembly process can be used for solving the 0-1 multi-objective knapsack problem by mainly constructing four small systems which are nondeterministic guess system, multiplication system, addition system and comparing system, by which we can probabilistically get the feasible solution of the problem. Our model can successfully perform the 0-1 multi-objective knapsack problem in polynomial time with optimal Theta(1) distinct tile types, parallely and at very low cost.
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