This paper focuses on extracting effective vitrinite reflectance features, and selecting the most important features to predict coke quality. Feature extraction method based on Gaussian model is proposed, which can ex...
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This paper focuses on extracting effective vitrinite reflectance features, and selecting the most important features to predict coke quality. Feature extraction method based on Gaussian model is proposed, which can extract vitrinite reflectance features, the vitrinite reflectance features and traditional features are fused together to excavate the relationship between coal and coke quality. Then Xgboost is used as a new feature selection method to measure features importance and remove the redundant features. Finally, high correlation features are selected as input variables to predict coke quality, which can enhance prediction performance and stability. Experimental results show that the proposal outperforms prediction model based on traditional indicators.
This paper investigates the stability of linear systems with a time-varying delay. We propose a new approach to construct Lyapunuv-Krasovskii functional (LKF). Compared with other traditional approach, the proposed on...
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This paper presents a maximum power point tracking controller for a PV solar system. The PV solar system is connected to the load through a DC-DC boost converter which is controlled by Adaptive Neuro-Fuzzy Inference S...
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Adaptive Dynamic Programming (ADP) with critic-actor structure is a useful way to achieve online learning control. The Gaussian-Kernel Function Adaptive Dynamic Programming (GK-ADP) algorithm does not need to preset t...
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Adaptive Dynamic Programming (ADP) with critic-actor structure is a useful way to achieve online learning control. The Gaussian-Kernel Function Adaptive Dynamic Programming (GK-ADP) algorithm does not need to preset the value function model which greatly enhances the applicability of ADP method in continuous space. However, when the complexity of the system increases in practice, the scale of sample set will increase which will induce a high computation cost. In order to speed up computation, a CUDA-Based Iterative Segmentary Gaussian-Kernel Function Adaptive Dynamic Programming algorithm( cuISGK-ADP) is presented in this paper. The algorithm uses singular value decomposition to decompose the large-scale matrix and uses CUDA with multi-threaded structure in order to enhance the performance. The comparison result illustrates that the computation burden which hinders the GK-ADP's application is reduced when the cuISGK-ADP algorithm is introduced. The proposed approach enhances the efficiency of the computation to a large extent.
This study presents a novel impact time and angle constrained guidance law for homing missiles. The guidance law is first developed with the prior-assumption of a stationary target, which is followed by the practical ...
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This study presents a novel impact time and angle constrained guidance law for homing missiles. The guidance law is first developed with the prior-assumption of a stationary target, which is followed by the practical extension to a maneuvering target scenario. To derive the closed-form guidance law, the trajectory reshaping technique is utilized and it results in defining a specific polynomial function with two unknown coefficients. These coefficients are determined to satisfy the impact time and angle constraints as well as the zero miss distance. Furthermore, the proposed guidance law has three additional guidance gains as design parameters which make it possible to adjust the guided trajectory according to the operational conditions and missile's capability. Numerical simulations are presented to validate the effectiveness of the proposed guidance law. (C) 2016 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
An estimate-and-forward(EF) scheme for single-input single-output(SISO) and multiple-input multiple-output(MIMO) full-duplex two-way relay networks is proposed and analyzed. The relay estimates the received signal fro...
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An estimate-and-forward(EF) scheme for single-input single-output(SISO) and multiple-input multiple-output(MIMO) full-duplex two-way relay networks is proposed and analyzed. The relay estimates the received signal from two terminal nodes by a minimum mean squared error(MMSE) estimation and forwards a scaled version of the MMSE estimate to the destination. The proposed EF outperforms conventional amplify-and-forward(AF) and decode-and-forward(DF) across all signal-to-noise ratio(SNR) region. Because its computational complexity is high for relays with a large number of antennas(large MIMO) and/or high order constellations, an approximate EF scheme, called list EF, are thus proposed to reduce the computational complexity. The proposed list EF computes a candidate list for the MMSE estimate by using a sphere decoder, and it approaches the performance of the exact EF relay at a negligible performance loss. The proposed forwarding approach also could be used to other relay networks, such as half-duplex, one-way or massive MIMO relay networks.
Forest fires are serious disasters that endanger the safety and property of residents. To deal with the arson-caused forest fires, we use security game theory to generate optimal patrol strategy under limited patrolli...
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Forest fires are serious disasters that endanger the safety and property of residents. To deal with the arson-caused forest fires, we use security game theory to generate optimal patrol strategy under limited patrolling resources. The existing security game algorithms focus on a single behavior model to prevent attacks, while our work is to incorporate the secondary damage caused by the attack behavior into the optimization object. For forest fires, the security game algorithm only expects to catch arsonists in the forest, which is unreasonable in our opinion. Our algorithm incorporates the spread of fires into patrolling path planning so that defenders avoid being swallowed by fire via capturing the spread of it.
This paper concerns disturbance rejection for a repetitive-control system(RCS) with unknown time-varying uncertainties and nonlinearity. The design of the RCS is based on the concept of equivalent input disturbance...
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ISBN:
(纸本)9781538629185
This paper concerns disturbance rejection for a repetitive-control system(RCS) with unknown time-varying uncertainties and nonlinearity. The design of the RCS is based on the concept of equivalent input disturbance(EID). First, an EID estimator is constructed through a state observer with dynamic coefficient matrix that effectively estimates the total effect of the uncertainties and nonlinearity on the output of the plant. Next, a robust globally uniformly ultimately bounded stability condition for the EID-based RCS is derived in the form of a linear matrix inequality. Then, the methods of designing a modified repetitive controller, a state-feedback controller, and an EID estimator are explained. Finally, simulation results demonstrate the validity of the method.
The real-time state estimation becomes greatly important with the wide application of phasor measurement unit (PMU) in distributed generation (DG) for wide-area measurement systems (WAMS). In view of estimation, parti...
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ISBN:
(纸本)9781538626191
The real-time state estimation becomes greatly important with the wide application of phasor measurement unit (PMU) in distributed generation (DG) for wide-area measurement systems (WAMS). In view of estimation, particle filter (PF) is capable of providing the best performance but at the cost of heavy computation burden. Besides, the growing grid size sustainably boosts the amount of data communication from PMU, causing the congestion. An event-trigger master-slave nonlinear filter (ET-MSNF) is proposed to guarantee the estimation accuracy and get the communication bandwidth relieved. The local slave filter at the generator node carries out the local estimation and event-trigger strategy using unscented transformation, which is identical to the center slave. The master filter at the center is designed using Monte Carlo method to improve the center's estimation accuracy by the cooperation with the center slave. Such master-slave filtering structure can fully utilize the computation capability both at the center and node. Simulation on the standard IEEE 39-bus system verify the performance of ET-MSNF.
The network structure and functional properties of gene regulatory system and their relationships are an important research field in systems *** this paper,a new improved model is proposed based on the study of gene e...
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The network structure and functional properties of gene regulatory system and their relationships are an important research field in systems *** this paper,a new improved model is proposed based on the study of gene expression *** model takes into account the effect of protein concentration on the gene expression,so as to obtain a new bifurcation point and improve the performance of the *** validity of the model is verified by theoretical analysis and data simulation.
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