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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Hai-Peng Ren Xuan Wang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xian China

Due to the advantages of strong carrying capacity and fast response speed, hydraulic servo system has been widely used in industrial motion control field. The hydraulic servo system is susceptible to the nonlinearity, parameter uncertainty and unknown disturbance, which makes the high performance position control of the hydraulic servo system become a challenge. In this paper, considering the hydraulic position servo control system with input saturation, a sliding mode variable structure controller with shrinking boundary layer is designed. The proposed method is used to experimentally track three kinds of reference signals based on Programmable Logic controller (PLC), i.e., S7-200PLC, and hydraulic control system provided by Festo company. The experiment results indicate that the proposed method is effective and achieves smaller steady state tracking error as compared with sign function robust item and the conventional PID control.

关键词： Servomotors Cavity resonators Valves Force Touch sensitive screens

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Optimizing multi-criteria k-shortest paths in graph by a natural routing genotype-based genetic algorithm

Optimizing multi-criteria k-shortest paths in graph by a nat...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Yang Wang Qing Liu Haipeng Ren Xuan Ma Long Liu Wenqing Wang Jing Zhang Department of Information and Control Engineering Xi'an University of technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

k-shortest path problem (KSP) is a more general form of the classical shortest path problem in graph. Its task is no longer to find the shortest path between two vertices, but to find the shortest k paths. So far, the reported KSP-algorithms only considers finding shortest k paths with regard to a single criterion, while far more application scenarios of the KSP require to determine k paths by taking more criteria into account. This article formulates the KSP as a multi-objective optimization problem. In consideration of the problem's property and genetic algorithm's great success in multi-objective optimization, the genetic algorithm is utilized as the optimization tool. The genotype is directly represented as the form of natural routing. In order to make the related genetic operators risk-free, the conception of gene-bank is introduced. And the crossover and mutation are both implemented based on the introduced gene-bank. The proposed genetic algorithm is tested on an undirected graph of 9-vertex/65-edge. The testing result shows that, our proposed algorithm is valid and outperforms some other swarm intelligence-based algorithms in terms of the obtained paths' quality.

关键词： Genetic algorithms Optimization Genetics Routing Task analysis Encoding Sociology

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Vehicle detection based on point cloud intensity and distance clustering

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Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zhao Wang Xing Wang Bin Fang Kun Yu Jie Ma School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China National key laboratory of multispectral information processing technology Huazhong University of Science and Technology Wuhan 430074 China Science and technology on complex system control and intelligent agent cooperation laboratory Beijing 100074 China

In the intelligent transportation system, vehicle detection is one of the essential technologies in obstacle avoidance and navigation, however the existing vehicle detection methods cannot meet the actual needs. This paper presents a vehicle detection method combines the intensity and distance information of point cloud, which improves the segmentation performance of nearby objects. Specifically, the data of point cloud collected by lidar is preprocessed first. Then the processed point cloud is clustered by combining its coordinate and intensity information. Finally, the clustered suspected targets are fed to the random forest classifier. Our method can efficiently detect and classify targets in large-scale disordered 3D point cloud with high accuracy. In the real-scanned Livox Mid-40 Lidar dataset, our proposed method improves the detection accuracy by 31% compared with the traditional Euclidean clustering.

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Modeling and simulation of MHD melt convection and heat transfer in CZ crystal growth

Modeling and simulation of MHD melt convection and heat tran...

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Chinese Automation Congress

作者： Ni Zhang Ding Liu Weichao Huang National and Local Joint Engineering Shaanxi key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

This paper presents an axisymmetric swirl incompressible thermal lattice Boltzmann model to study the magnetohydrodynamics (MHD) melt flow and heat transfer at high Grashof number and high Reynolds number under external magnetic field in Czochralski (CZ) crystal growth process. The model is built based on the double distribution function lattice Boltzmann equation (DDF-LBE) and is verified by benchmark problem. By using the proposed model, the evolution relationship of melt flow, temperature is constructed under the combined effects of Lorenz force, rotating inertia force and thermal buoyancy force. Furthermore, the flow patterns and the temperature distribution of silicon melt under different magnetic field strengths are simulated. The simulation results show that with the increase of magnetic field strength, the melt velocity is reduced, which suppresses the melt convection and is beneficial for suppressing the fluctuation of melt. And the temperature gradient below the crystal growth interface increases in the case of crystal rotation, which is helpful to increase the crystallization rate. The combination of Cusp magnetic field, crucible rotation and crystal rotation can be used as an effective method in the production of high-quality crystal.

关键词： Modeling Computer simulation Crystal growth Lattice boltzmann method

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A multi-objective particle swarm optimization for multiple knapsack problem with strong constraints

A multi-objective particle swarm optimization for multiple k...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xuan Ma Ying Yan Qing Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an City China

Aiming at the characteristics of strong constraints of multiple knapsack problem (MKP), a method based on multi-objective particle swarm optimization is proposed in this paper. We take constraint violation as an optimal objective to avoid the troublesome of dealing with unfeasible solutions unsatisfied constraints. For updating effectively the external archive, the degree of constraint violation and the crowding degree of non-dominated particle in Pareto front are taken as two criteria. To decrease the probability of algorithm converging to a pseudo Pareto front, a mutation operator is designed. The experimental results of solving a number of MKP instances demonstrate that the proposed algorithm performs better to the MKP instances with strong constraints.

关键词： Optimization Sociology Statistics Particle swarm optimization Heuristic algorithms complex systems control systems

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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Water supply prediction based on initialized attention residual network

arXiv

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arXiv 2019年

作者： Long, Yuhao Wang, Jingcheng Wang, Jingyi Automation Department Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University Xi'an Shaanxi710021 China

Real-time and accurate water supply forecast is crucial for water plant. However, most existing methods are likely affected by factors such as weather and holidays, which lead to a decline in the reliability of water supply prediction. In this paper, we address a generic artificial neural network, called Initialized Attention Residual Network (IARN), which is combined with an attention module and residual modules. Specifically, instead of continuing to use the recurrent neural network (RNN) in time-series tasks, we try to build a convolution neural network (CNN) to recede the disturb from other factors, relieve the limitation of memory size and get a more credible results. Our method achieves state-of-the-art performance on several datasets, in terms of accuracy, robustness and generalization ability. Copyright © 2019, The Authors. All rights reserved.

关键词： Water supply

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The research of a novel single-phase three-level inverter circuit with its modulation strategy

The research of a novel single-phase three-level inverter ci...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jiangjiang Li Qi Zhang Xiangdong Sun School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Processing Xi'an China

This paper proposes a new single-phase three-level inverter topology and describes the control method for the proposed inverter. The inverter contains a H-bridge inverter circuit and an auxiliary circuit. The auxiliary circuit enables H-bridge circuit to be operated in the mode of five kinds of voltage level with unipolar pulse width modulation (PWM) strategy. The operation principle of proposed inverter topology is analyzed in detail. The proposed inverter eliminates the problems of DC capacitors voltage unbalance without additional control. The control of inverter is simple and easy to implement. And it is suitable for small or medium power applications. In this paper, the proportional-resonant (PR) controller is used in the proposed inverter, the feasibility and the analysis of principle of the proposed inverter is verified by simulation. The results show that the proposed inverter can output currents of low total harmonic distortion and has higher efficiency than the H-bridge inverter.

关键词： Inverters Capacitors Integrated circuits Mathematical model Topology Switches Modulation

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Learning oriented cross-entropy approach to user association in load-balanced HetNet

arXiv

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arXiv 2018年

作者： Huang, Xietian Xu, Wei Xie, Guo Jin, Shi You, Xiaohu Southeast University Nanjing China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'An University of Technology Xi'an China

This letter considers optimizing user association in a heterogeneous network via utility maximization, which is a combinatorial optimization problem due to integer constraints. Different from existing solutions based on convex optimization, we alternatively propose a cross-entropy (CE)-based algorithm inspired by a sampling approach developed in machine learning. Adopting a probabilistic model, we first reformulate the original problem as a CE minimization problem which aims to learn the probability distribution of variables in the optimal association. An efficient solution by stochastic sampling is introduced to solve the learning problem. The integer constraint is directly handled by the proposed algorithm, which is robust to network deployment and algorithm parameter choices. Simulations verify that the proposed CE approach achieves near-optimal performance quite efficiently. Copyright © 2018, The Authors. All rights reserved.

关键词： Heterogeneous networks

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Adaptive Generalized Projective Synchronization of a New Fractional Chaotic system with uncertain parameters

Adaptive Generalized Projective Synchronization of a New Fra...

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第30届中国控制与决策会议

作者： Jiaoru Huang Kun Zhong Fucai Qian The International Joint Research Center of Autonomous Systems and Intelligent Control Xi'an Technological University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

This paper investigates the generalized projective synchronization scheme of a new fractional chaotic system, which can display a four-wing chaotic attractor when the order of system is in the range of 0.82 and ***, considering the situation with unknown parameters, an adaptive nonlinear controller is obtained for synchronization and parameters identification based on fractional-order Lyapunov stability theorem. The fractional-order adaptation law, which can update parameters estimation errors online, is derived to ensure the stability of synchronization error system. Numerical simulations are used to verify the results.

关键词： Four-wing chaotic attractors uncertain parameter generalized projective synchronization parameter identification

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