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IEEE Conference on Vehicular Technology (VTC)

作者： Shuhuan Wen F. Richard Yu Key Laboratory of Industrial Computer Control Engineering of Hebei Yanshan University Qinhuangdao China Department of Systems and Computer Engineering Carleton University Ottawa ONT Canada

Coordinated multipoint (CoMP) communication is a new method that improves energy efficiency, extends cell coverage, and increases capacity in cellular networks. However, since channel state information from the involved cells is needed in CoMP systems, practical systems that employ CoMP techniques suffer from constraints imposed by the backhaul network. In this paper, we take a novel approach to study the energy efficiency issues in cooperative wireless cellular networks with CoMP communications. Specifically, to derive the base station grouping decisions for energy-efficient transmissions in CoMP, we use stochastic predictive control algorithm. Simulation results are presented to show the effectiveness of the proposed scheme.

关键词： Base stations Wireless communication Prediction algorithms Predictive control Delay Channel state information Predictive models

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Iterative learning control for nonlinear systems with uncertain state delay and arbitrary initial error

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控制理论与应用（英文版） 2011年第4期9卷 541-547页

作者： Hongbin WANG Yan WANG Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao Hebei 066004 China

Most of the existing iterative learning control algorithms proposed for time-delay systems are based on the condition that the time-delay is precisely available, and the initial state is reset to the desired one or a fixed value at the start of each operation, which makes great limitation on the practical application of corresponding results. In this paper, a new iterative learning control algorithm is studied for a class of nonlinear system with uncertain state delay and arbitrary initial error. This algorithm needs to know only the boundary estimation of the state delay, and the initial state is updated, while the convergence of the system is guaranteed. Without state disturbance and output measurement noise, the system output will strictly track the desired trajectory after successive iteration. Furthermore, in the presence of state disturbance and measurement noise, the tracking error will be bounded uniformly. The convergence is strictly proved mathematically, and sufficient conditions are obtained. A numerical example is shown to demonstrate the effectiveness of the proposed approach.

关键词： Iterative learning control State-delay system Initial condition Uncertain disturbances

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Bearing fault diagnosis based on multiple classifiers group of Fuzzy C Means

Bearing fault diagnosis based on multiple classifiers group ...

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Chinese control Conference (CCC)

作者： Li Xinbin Sun Xi Chen Yun Qiang key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9781467325813

In this paper, Fuzzy C-Means (FCM) is adopted to constitute multiple classifiers group to classify the bearing failure and its clustering centers are optimized by Particle Swarm Optimization (PSO) algorithm with global optimization and fast convergence characteristics. Classification recognition rate obtained by FCM is integrated by fuzzy integral information fusion system to gain the final result, in which fuzzy measure also is optimized by the PSO algorithm. Simulation of identifying the bearing inner race, outer race and rolling bodies fault, the results show that the classifier improves the recognition accuracy rate of the fault diagnosis.

关键词： Fault diagnosis Electronic mail Educational institutions Particle swarm optimization Classification algorithms Clustering algorithms Sun

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Sparse online LS-SVM based on modified particle swarm optimization algorithm and application

Sparse online LS-SVM based on modified particle swarm optimi...

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International Conference on Intelligent control and Information Processing (ICICIP)

作者： Weiping Zhang Peifeng Niu Guoqiang Li Institute of Electrical Engineering Qinhuangdao Institute of Technology Yanshan University China key Laboratory of Industrial Computer Control Engineering of Hebei Province National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Rolling China Institute of Electrical Engineering Yanshan University China

In this paper, A simple and effective mechanism is proposed to realize the parsimoniousness of the online least squares support vector machine. Hence, the response time is curtailed. Besides, a modified Particle Swarm Optimization (PSO) algorithm is proposed to ascertain the optimal model parameters. Simulation results show that it outperforms GA and common PSO algorithms and LS-SVM model based on the modified PSO algorithm has the best regression accuracy and generalization ability. The sparse online LS-SVM algorithm is applied to build a turbine heat rate forecasting model, which possesses dynamic prediction functions.

关键词： Prediction algorithms Heating Mathematical model Training Computational modeling Support vector machines Optimization

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A cooperation strategy based on bargaining solution in wireless sensor networks

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控制理论与应用（英文版） 2011年第1期9卷 121-126页

作者： Ma, Kai Guan, Xinping Zhao, Bin Wang, Juan Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao Hebei 066004 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China

This paper presents a symmetric cooperation strategy for wireless sensor networks, aiming to improve the transmission efficiency of the network. The cooperation strategy is implemented by partitioning the nodes into several cooperative groups. Then, in each group, the optimal cooperative bandwidth allocation is obtained based on Raiffa-KalaiSmorodinsky bargaining solution (RBS). Numerical results show that the symmetric cooperation strategy can improve the sensor node’s transmission efficiency dramatically.

关键词： Wireless sensor networks Cooperative diversity Bargaining solution Bandwidth allocation

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Multi-user Symmetric Cooperation Based on Nash Bargaining Solution in Cooperative Relay Networks

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International Journal of Automation and computing 2011年第4期8卷 452-458页

作者： Kai Ma Xin-Ping Guan Juan Wang Xiao-Min Wei Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 PRC School of Electronics Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 PRC

This paper presents a symmetric cooperation strategy for cooperative relay networks with multiple users. The multi-user symmetric cooperation model and the relay selection algorithm are proposed. Then, the time slot allocation problem is cast into a bargaining problem, and the optimal time slot allocation solution is obtained by Nash bargaining solution （NBS）. Moreover, we also consider the implementations of the cooperation strategy, i.e., the grouping and admission control algorithm. Simulation results show that users can obtain larger rates under the symmetric cooperation strategy than the non-cooperative case.

关键词： Cooperative relay Nash bargaining solution （NBS） time slot allocation relay selection admission control.

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Sensor selection for received signal strength-based source localization in wireless sensor networks

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控制理论与应用（英文版） 2011年第1期9卷 51-57页

作者： Zhao, Bin Guan, Xinping Xie, Lihua Xiao, Wendong Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao Hebei 066004 China School of Electronics Information and Electrical Shanghai Jiao Tong University Shanghai 200240 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Institute for Infocomm Research Singapore 138632 Singapore

Generally, localization is a nonlinear problem, while linearization is used to simplify this problem. Reasonable approximations could be achieved when signal-to-noise ratio (SNR) is large enough. Energy is a critical resource in wireless sensor networks, and system lifetime needs to be prolonged through the use of energy efficient strategies during system operation. In this paper, a closed-form solution for received signal strength (RSS)-based source localization in wireless sensor network (WSN) is obtained. A sensor selection method is proposed to improve the localization accuracy as well as to save energy consumption. By selecting only a limited number of sensor nodes based on the model accuracy and geometry structure analysis, localization performance is improved, and energy consumption is reduced. In addition, extensive simulations are presented to demonstrate that the estimation performance with the proposed sensor selection method is better than that without sensor selection.

关键词： Received signal strength Source localization Closed-form solution Sensor selection Geometry structure

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Joint power and carrier allocation for cognitive radio networks based on OFDMA

Joint power and carrier allocation for cognitive radio netwo...

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Chinese control Conference (CCC)

作者： Xiaomin Wei Kai Ma Bin Zhao Xiaoyuan Luo Xinping Guan Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

This paper is concerned with the joint power and carrier allocation problem in cognitive radio networks based on OFDMA. Considering the limit of the throughput for original resource allocation algorithm, we propose the improved framework, in which the secondary user can transmit with a proper power as the primary user is active. Numerical results show that the proposed algorithm can improve the throughput of the network effectively.

关键词： Cognitive radio Resource management Electronic mail Sensors Joints computer networks

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Cooperative spectrum sensing for cognitive radios based on a PA-GABC algorithm

Cooperative spectrum sensing for cognitive radios based on a...

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International Conference on Electronics, Communications and control (ICECC)

作者： Xinbin Li Lei Liu Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yan Shan University Qinhuangdao China

Spectrum sensing plays a critical role in cognitive radio networks. A good sensing scheme can reduce the false alarm probability and increase the detection probability, and thus improves utilization. In this paper, in order to avoid the defect that cooperative spectrum sensing based on Particle Swarm Optimization (PSO) algorithm is easy to trap into a local optimization. We propose a population adaptive Gbest-guided artificial bee colony (PA-GABC) algorithm and it is applied to cooperative spectrum sensing for cognitive radios field. Simulations are performed to compare the performance of the PA-GABC algorithm and traditional artificial bee colony (ABC) algorithm. The performance of the proposed cooperative spectrum sensing method based on the PA-GABC and that of the cooperative spectrum sensing method using particle swarm optimization (PSO) algorithm are also compared. Results show that the proposed PA-GABC-based cooperative spectrum sensing method is efficient and stable, and it gets higher detection probability than the ABC-based method and the PSO-based method under the same probability of false alarm.

关键词： Sensors Cognitive radio Algorithm design and analysis Optimization Signal processing algorithms Particle swarm optimization Electrical engineering

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Fault search based on grey fuzzy multi-attribute decision-making

Fault search based on grey fuzzy multi-attribute decision-ma...

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International Conference on Fluid Power and Mechatronics (FPM)

作者： Chengyu Yao Zhen Dang Dongning Chen Shijun Lv Key Laboratory of Industrial Computer Control Engineering of Hebei Yanshan University Qinhuangdao China Key Laboratory of Heavy Machinery Fluid Power Transmission and Control of Hebei Province Yanshan University Qinhuangdao China

In order to overcome the characteristics of uncertainty and incomplete information of fault attribute in searching for fault, a new fault search method based on the fault tree and grey fuzzy multi-attribute decision-making is proposed in this paper. Firstly, utilizing fault tree analysis (FTA) method to determine the initial fault alternative, fault probability and search cost of the fault alternative are considered as fault attributes simultaneously, the attribute value of fault alternative is described as grey fuzzy numbers, calculating the attribute weight by the information entropy method. Then, the grey relational grade between the fault alternative and the ideal alternative is calculated base on grey relational analysis method, and relative closeness of fault alternative is achieved. Finally, according to the relative closeness determine the search order of all fault alternatives. An engineering example of the hydraulic suspension system of a certain type truck is adopted to demonstrate the feasibility and accuracy of the proposed method.

关键词： Decision making Fault trees Suspensions Search methods Pragmatics Fault diagnosis Manganese

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