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第35届中国控制会议

作者： TIAN Ya CHEN Wenjie Department of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781509009107

Data mining is one hot orientation in today’s research *** activity recognition is meaningful in our daily living and is a significant aspect in data *** previously research is almost based on tri-axial *** paper presents a novel method to collect data from both accelerometer and gyroscope using *** daily activities including Walking,Running,Upstairs,Downstairs,Standing,Sitting and Cycling,a total of seven categories are *** raw data from MEMS are recorded by smartphone according to different daily *** improve the accuracy of classification for daily activities,this paper combines time-series features with wavelet coefficients to extract *** recognize these activities,the support vector machine is used to finish this ***,we compare the accuracy with other machine learning methods,such as k-nearest neighbor algorithm and neural network or decision *** result indicates that our method can achieve nearly 96%classification accuracy for the seven kinds of daily activities.

关键词： classification activity recognition wavelet transform support vector machine feature extraction

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BP-PID control Applied in Evaporator of Organic Rankine Cycle system

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Instrumentation 2017年第3期4卷 54-58页

作者： WANG Zhigang GUO Shuang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering & National Demonstration Center for Experimental Mechanical and Electrical Engineering Education & Tianjin University of Technology

According to the problem that the selection of traditional PID control parameters is too complicated in evaporator of Organic Rankine Cycle system(ORC),an evaporator PID controller based on BP neural netw ork optimization is designed. Based on the control theory,the model of ORC evaporator is set up. The BP algorithm is used to control the Kp,Kiand Kdparameters of the evaporator PID controller,so that the evaporator temperature can reach the optimal state quickly and steadily. The M ATLAB softw are is used to simulate the traditional PID controller and the BP neural netw ork PID controller. The experimental results show that the Kp,Kiand Kdparameters of the BP neural netw ork PID controller are 0. 5677,0. 2970,and 0. 1353,***,the evaporator PID controller based on BP neural netw ork optimization not only satisfies the requirements of the system performance,but also has better control parameters than the traditional PID controller.

关键词： Organic Rankine Cycle PID controller Evaporator BP Neural Network

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An Improved Levenberg-Marquardt Algorithm with Adaptive Learning Rate for RBF Neural Network 35

An Improved Levenberg-Marquardt Algorithm with Adaptive Lear...

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第35届中国控制会议

作者： AN Ru LI Wen Jing Han Hong Gui QIAO Jun Fei College of Electronic and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

In this paper,an improved Levenberg-Marquardt(LM) algorithm with adaptive learning rate is proposed to optimize the learning process of RBF neural ***,an improved LM algorithm is adopted using a quasi-Hessian matrix and gradient vector which are computed *** with the conventional LM algorithm,Jacobian matrix multiplication and storage are not required in the improved LM algorithm,which can reduce computation cost and solve the problem of memory ***,the adaptive learning rate is integrated into the improved LM algorithm in order to accelerate the convergence speed of training algorithm and improve the network performance of nonlinear system ***,several experiments are conducted and the results show that the proposed method has faster convergence speed and better prediction performance.

关键词： Improved LM algorithm RBF neural network adaptive learning rate fast convergence speed

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Design of a Self-organizing Recurrent RBF Neural Network Based on Spiking Mechanism 35

Design of a Self-organizing Recurrent RBF Neural Network Bas...

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第35届中国控制会议

作者： LU Chao HAN Honggui QIAO Junfei YANG Cuili College of Electronic and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

Based on the systemic investigation of recurrent neural network,a self-organizing recurrent radial basis function(SR-RBF) neural network which based on the spiking mechanism and improved Levenberg-Marquardt(LM) algorithm is proposed in this *** hidden neuron in the recurrent radial basis function(RRBF) can be added or pruned by computing the spiking strength of the connections between hidden and output neurons of RRBF neural ***,to ensure the accuracy of SR-RBF neural network,the parameters are trained by improved LM *** SR-RBF neural network is used for approximating the time-series prediction and classical non-linear ***,comparisons with other methods demonstrate that the SR-RBF neural network is more effective in terms of accuracy,generalization,and network structure.

关键词： Self-organizing spiking mechanism recurrent radial basis function time-series prediction

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Unit commitment considering demand response behavior based on utility maximization

Unit commitment considering demand response behavior based o...

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2017 IEEE Conference on Energy Internet and Energy system Integration, EI2 2017

作者： Zhang, Yumin Han, Xueshan Xu, Bo Zhang, Li Sun, Donglei Miao, Xiaofeng Jiang, Jiayin Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Haidian District Beijing100084 China Economic and Technology Research Institute of State Grid Shandong Electric Power Company Jinan China State Grid Shandong Electric Power Company Yantai Electric Power Company Yantai264001 China

ISBN: (纸本)9781538614273

The active participation of demand side resources in power grid operation not only benefits the individual participant but also benefits the whole system. The optimal goal can promote by excavating the active behaviors of demand side. The welfare maximization of market participant is the driving force of such active behaviors. Considering the independence of each user's behavior, the consumer's utility function is selected to depict consumer's preference and demand response behavior. In order to coordinate the consumers' maximum welfare with social welfare maximization, consumers' utility function and units' operation cost are integrated into Unit Commitment (UC) model. The objective function is to maximize social welfare, by subtracting units' operation cost from consumers' total utility, and this objective can be acquired. Considering the proposed model should be solved in a distributed manner, the idea of the centralized coordination and the decentralized decision-making is proposed. Based on the Lagrangian relaxation (LR) principle and distributed real-time pricing scheme, a closed-loop feedback mechanism is constructed to reflect the relationship among generator output, price level, and load demand. The ten generating units example can illustrate the effectiveness of the proposed method. © 2017 IEEE.

关键词： Power markets

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CTMC-based numerical analysis of cluster system with middle states in the case of common mode failure

CTMC-based numerical analysis of cluster system with middle ...

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International Conference on Computer and Information Science (ACIS)

作者： Zhiguo Hong Minyong Shi Yongbin Wang Faculty of Science and Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing China Beijing Key Laboratory of Modern Entertainment Technology Beijing China

ISBN: (纸本)9781509055081

By taking both CMF (Common Mode Failure) and middle states into account, numerical analysis of availability of cluster system is analyzed. Firstly, a CTMC (Continuous Time Markov Chain) model of cluster system containing three cluster nodes is constructed with failure rate (λ), repair rate (μ), CMF rate (γ), reconfiguration rate (β) and reset rate (δ) etc. Then the steady state solution of the CMTC model is concerned by solving the equations with the combination of several parameters. Subsequently, the effect of probability of being in automatic recovery mode (k) on availability of cluster system is analyzed and discussed via numerical values-based chart thereby. This work offers quantitative analysis of cluster system's availability.

关键词： Mathematical model Analytical models Numerical models Markov processes Steady-state Computers Reliability

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Enhanced Geometric Map:a 2D&3D Hybrid City Model of Large Scale Urban Environment for Robot Navigation

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机器人 2016年第3期38卷 311-321页

作者： LI Haifeng HU Zunhe LIU Jingtai College of Computer Science and Technology Civil Aviation University of China Tianjin 300300 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou 350121 China Institute of Robotics and Information Automatic System Nankai University Tianjin 300071 China Tianjin Key Laboratory of Intelligent Robotics Tianjin 300071 China

To facilitate scene understanding and robot navigation in large scale urban environment, a two-layer enhanced geometric map(EGMap) is designed using videos from a monocular onboard camera. The 2D layer of EGMap consists of a 2D building boundary map from top-down view and a 2D road map, which can support localization and advanced map-matching when compared with standard polyline-based maps. The 3D layer includes features such as 3D road model,and building facades with coplanar 3D vertical and horizontal line segments, which can provide the 3D metric features to localize the vehicles and flying-robots in 3D space. Starting from the 2D building boundary and road map, EGMap is initially constructed using feature fusion with geometric constraints under a line feature-based simultaneous localization and mapping(SLAM) framework iteratively and progressively. Then, a local bundle adjustment algorithm is proposed to jointly refine the camera localizations and EGMap features. Furthermore, the issues of uncertainty, memory use, time efficiency and obstacle effect in EGMap construction are discussed and analyzed. Physical experiments show that EGMap can be successfully constructed in large scale urban environment and the construction method is demonstrated to be very accurate and robust.

关键词：被提高的几何学的地图都市模型机械手航运同时发生的定位而且映射局部的包裹调整

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Multi-objective Design of the Water Distribution systems Using SPEA2 35

Multi-objective Design of the Water Distribution Systems Usi...

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第35届中国控制会议

作者： MENG Qinchao QIAO Junfei YANG Cuili College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

As a complicated and combinatorial optimization problem, the design of Water distribution systems(WDSs) is difficult to be solved. In this paper, in order to design WDSs better, three objectives are considered, including the initial construction cost, the sum of node surplus head and the variance of node surplus head. The consideration of the variance of node surplus head can reflect the distribution of the node surplus head in WDSs. This problem is solved by the strength pareto evolutionary algorithm(SPEA2). Finally, the model is applied into two well-known benchmark case studies, the two-loop network and the New York Tunnels network. By comparing with some algorithms, such as Tabu search algorithm and non-dominated sorting genetiv algorithm(NSGA2), the performance of SPEA2 shows the effectiveness in terms of reliability, convergence, as well as diversity.

关键词： Multi-objective optimization Water distribution systems SPEA2

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Kinematic Modeling and Error Analysis of the Six Pole Parallel Robot

Kinematic Modeling and Error Analysis of the Six Pole Parall...

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2016 IEEE Advanced Information Management,Communicates,Electronic and Automation control Conference(IMCEC 2016)

作者： ZHAO Xin-hua LUAN Qian-qian ZHAO Lei WANG Shou-jun GE Wei-min FAN Meng-ran Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronic System Tianjin University of Technology School of Mechanic Engineering

ISBN: (纸本)9781509001668

The parallel manipulator has some advantages of high accuracy,high speed and high stiffness *** makes up for the shortcomings of serial *** the parallel mechanism becomes a potential motion platform with high speed and high *** poles parallel robot improves these defects of more singularity,poor load capacity and low stiffness which exist in workspace of the classic plane five poles parallel *** and forward kinematic models are established based on the structure of the *** influence of foundation beds' location error,driving angle error and rod processing error on control accuracy is systematically *** theoretical foundation has been provided for realizing the optimal design of the robot and control in high accuracy.

关键词： high speed parallel robot kinematics error analysis

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Prediction of PM2.5 based on Elman neural network with chaos theory 35

Prediction of PM2.5 based on Elman neural network with chaos...

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第35届中国控制会议

作者： HU Zhiqiang LI Wenjing QIAO Junfei College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

PM2.5 is difficult to accurately forecast due to the influence of multiple meteorological and pollutant variables in the complex nonlinear dynamic atmosphere *** this paper,an Elman neural network prediction method based on chaos theory is put forward for the ***,the chaotic characteristics of the concentration of the PM2.5 are analyzed and verified from the correlation dimension,the maximum Lyapunov exponent and the Kolmogorov ***,phase space reconstruction technique of chaotic theory is adopted to reconstruct the phase space of PM2.5 time *** reconstructed phase space and the future concentration of PM2.5 are taken as the input and output of the Elman neural network with chaos theory(Elman-chaos) *** numerical and experimental analyses show that this method is proportionally superior to that without considering the chaos characteristics and other *** Elman-chaos prediction model has better prediction performance and application value.

关键词： PM2.5 Chaos Phase space reconstruction Elman neural network Prediction

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