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第25届中国控制与决策会议

作者： Fei Ling Wang Jingcheng Ge Yang Li Chuang Zhang Langwen Department of Automation Shanghai Jiaotong University and Key Laboratory of System Control and Information Processing Ministry Of Education Of China

ISBN: (纸本)9781467355339

Many researches on the prediction of the penetration rate of the tunneling boring machine (TBM) have been carried out. The prediction of the penetration rate will contribute to reduce the danger of TBM construction, decrease the cost and provide the support for the construction planning. Most methods for predicting penetration rate rely on the fixed equation relationship between the input parameters and output parameters. In this paper, we build up a dynamic model. We mainly make use of the partial least squares regression algorithm (PLS) and the structure of the fuzzy-neuron network (FNN) to build up the model. All the data should be normalized. We randomly select 120 groups of the data from TBM construction as the training data and 33 groups of data as the testing data. The training and testing results are analyzed by the mean square error and the correlation coefficient. At the same time, we compare the prediction of the PLS-FNN model with the prediction of the FNN model. The simulation result shows that the PLS-FNN model has the good performance for the prediction.

关键词： TBM, Rate Of Penetration, PLS, Fuzzy-Neuron Network

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Hybrid Modeling and Optimization for Energy Management system of MicroGrid 35

Hybrid Modeling and Optimization for Energy Management Syste...

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第35届中国控制会议

作者： ZHENG Chaoyue LI Dewei XI Yugeng WANG Xi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781509009107

The MicroGrid(MG) is the important part of the SmartGrid system and the Energy Management system(EMS)determines the performance of a *** paper presents a generalized formulation to determine the optimal strategy and cost optimization of the EMS for a MicroGrid of the small-modular residential *** EMS includes the generating capacity of diesel generator,PV array,purchasing or selling electricity,and the state of battery-charging or *** paper proposes the optimization problem of the EMS,which is formulated as a mixed-integer quadratic programming(MIQP) *** the EMS,the predictions of the demand and the output of PVs are often inaccurate,and to solve this problem,this paper adopts rolling optimization to implement the EMS ***,the rolling optimization utilizes the multi-point radiation based parallel branch and bound(MPRP-BB) algorithm on GPU to improve the computational *** simulation results compare the advantages and disadvantages of the rolling optimization and global optimization,which verifies the effectiveness of the proposed method.

关键词： MicroGrid Energy Management system Mixed-integer Quadratic Programming MPRP-BB Algorithm GPU

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Deep Learning EEG Response Representation for Brain Computer Interface 34

Deep Learning EEG Response Representation for Brain Computer...

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第三十四届中国控制会议

作者： LIU Jingwei CHENG Yin ZHANG Weidong Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781467374439

In this paper, the multi-scale deep convolutional neural networks are introduced to deal with the representation for imagined motor Electroencephalography(EEG) signals. We propose to learn a set of high-level feature representations through deep learning algorithm, referred to as Deep Motor Features(Deep MF), for brain computer interface(BCI) with imagined motor tasks. As the extracted Deep MF are dissimilar for different tasks and alike for the same tasks, it is convenient to separate the diverse EEG signals for imagined motor tasks apart. Our approach achieves 100% accuracy for 4 classes imagined motor EEG signals classification on Project BCI- EEG motor activity dataset. Moreover, thanks to the highly abstract features Deep MF learned, only 4.125 seconds trials of training data are needed, compared with the conventional BLDA algorithm for 8.75 seconds trials demand to achieve the same accuracy, accordingly the BCI response time and the required trials for training are almost declined by half. Experiments are provided to illustrate the effectiveness of the proposed design approach.

关键词： deep learning,electroencephalography(EEG),brain computer interface(BCI),convolutional neural networks(CNNs)

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Model Predictive control for Household Energy Management based on Individual Habit

Model Predictive Control for Household Energy Management bas...

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第25届中国控制与决策会议

作者： Keyu Long Zaiyue Yang State Key Lab. of Industrial Control Technology Zhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781467355339

This paper focuses on the load shifting problem in a household scenario with a large-capacity battery. We propose a novel Model Predictive control （MPC） framework to control the charge/discharge power of battery, hence to shave the peak load. Being different from other studies, the framework is designed on the base of individual habit of energy consumption, as it is envisioned that the individual habit is critical for choosing the suitable energy services. In this paper, the habit is modeled as a Markov process and gradually learned by an iterative algorithm;thus, the habit can be utilized for the prediction of future energy consumption. Then, the rolling optimization is applied for the optimal control of the charge/discharge power of battery. It is shown by numerical simulations that the proposed approach can significantly reduce the peak load.

关键词： Habit Model Predictive control Markov Chain Nonlinear Optimization Household Energy Management

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Soft Robotics:Morphology and Morphology-inspired Motion Strategy

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1500-1522页

作者： Fan Xu Hesheng Wang Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

Robotics has aroused huge attention since the *** of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental ***,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured *** decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing *** presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific *** paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

关键词： Soft continuum manipulator soft gripper soft mobile robot soft robot control method soft robot modeling method soft robotics

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Bilateral Teleoperation of Multiple Agents with Formation control

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IEEE/CAA Journal of Automatica Sinica 2014年第2期1卷 141-148页

作者： Jing Yan Xian Yang Cailian Chen Xiaoyuan Luo Xinping Guan Institute of Electrical Engineering Yanshan University Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

This paper studies the formation problem for multislave teleoperation system over general communication networks,where multiple mobile slave agents are coupled with a single master robot. The forward and backward network transmission time delays are assumed to be asymmetric and *** to the quantization in the network, a dynamic quantization strategy is provided to quantize the output signals of the master robot and slave agents before transmitting. Then, a novel masterslave protocol is designed to achieve the formation task under variable time delays and quantization. Additionally, the sufficient conditions for stability are presented to show that the formation protocol can stabilize the master-slave system under variable time delays and quantization. Finally, simulation are performed to show effectiveness of the main results.

关键词： Robots Quantization (signal) Delay effects Protocols Stability analysis Delays Multi-agent systems

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Modelling Transcriptional Regulation with Fractional Order Differential Equation using Gaussian Process 35

Modelling Transcriptional Regulation with Fractional Order D...

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第35届中国控制会议

作者： JI Ruirui ZHANG Xinxin YAN Xiaomei School of Automation and Information Engineering Xi'an University of Technology Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

A reasonable math model is fundamental to describing gene regulatory mechanism.A new method is proposed to model transcriptional regulation with transcription factor from gene expression profiles using fractional order differential *** Process is employed as a tool to model the latent transcription factor activity and particle swarm optimization algorithm is utilized to optimize the fractional order,kinetic parameters in the model and hyperparameters in kernel *** results of the experiment on real gene expression profiles indicate that the fractional order differential equation fits data better,also the proposed approach is feasible to model transcriptional regulation.

关键词： Transcriptional regulation Fractional order differential equation Gaussian Process Particle swarm optimization

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Model-based Predictive control for Spatially-distributed systems Using Dimensional Reduction Models

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International Journal of Automation and computing 2011年第1期8卷 1-7页

作者： Meng-Ling Wang Ning Li Shao-Yuan Li Institute of Automation Shanghai Jiao Tong University Shanghai 200240 PRC Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 PRC

In this paper, a low-dimensional multiple-input and multiple-output （MIMO） model predictive control （MPC） configuration is presented for partial differential equation （PDE） unknown spatially-distributed systems （SDSs）. First, the dimension reduction with principal component analysis （PCA） is used to transform the high-dimensional spatio-temporal data into a low-dimensional time domain. The MPC strategy is proposed based on the online correction low-dimensional models, where the state of the system at a previous time is used to correct the output of low-dimensional models. Sufficient conditions for closed-loop stability are presented and proven. Simulations demonstrate the accuracy and efficiency of the proposed methodologies.

关键词： Spatially-distributed system principal component analysis （PCA） time/space separation dimension reduction model predictive control （MPC）.

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Doppler Scale Estimation for Underwater Acoustic Communications Using Dual Zadoff-Chu Sequences 8

Doppler Scale Estimation for Underwater Acoustic Communicati...

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8th IEEE International Conference on Signal processing, Communications and Computing, ICSPCC 2018

作者： Yu, Xiaowei Wang, Yiyin Guan, Xinping Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781538679463

Doppler scale estimation is prerequisite for underwater acoustic information transmission. This paper presents a Doppler scale estimation method based on a novel preamble, which is composed of dual Zadoff-Chu (ZC) sequences. The dual ZC sequence is a superposition of two orthogonal ZC sequences. The super-resolution technique is employed to estimate the Doppler scale information carried by the received preamble. Numerical simulations are included to compare the proposed method with the existing m-sequence based Doppler scale estimator. The simulation results show that the proposed method is superior to the m-sequence based method for the Doppler estimation. © 2018 IEEE.

关键词： Underwater acoustics

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HScore: A Target Attention-based Filter Pruning with Visualizing the Area of Feature Map

HScore: A Target Attention-based Filter Pruning with Visuali...

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International Neural Network Society Workshop on Deep Learning Innovations and Applications, INNS DLIA 2023

作者： Zhang, Chenrui Zhuang, Chenyi Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

Neural network pruning plays an important role in the deployment on resource-constrained devices by reducing the scale of the network and the computational complexity. Different from existing pruning methods that only consider the amount of information filters contain, we think the distribution of information is more important to the model accuracy. Then we use visualization of feature map to consider the impact of the attention area on the network decision. In order to directly relate the attention area with confidence score, we propose HScore to use interpolation and normalization to visualize the attention area of feature map and calculate the confidence score by putting only the attention area into the model. The principle behind is that if the feature map focuses on an area which can achieve a higher classification confidence, then the corresponding channel is important to keep the accuracy of model. The confidence score of attention area represents the importance of the channel to the model and filters with smaller confidences would be pruned. The experiment results prove that HScore can prune more redundant filters while maintaining better accuracy. Notably, our method can reduce 68.6% parameters and 73.0% FLOPs of ResNet-110 even with 0.14% top-1 accuracy increase on CIFAR-10. With ResNet-50, we achieve a 55% FLOPs reduction with only a loss of 1.03% in the top-1 accuracy on LSVRC-2012, which has advanced the state-of-the-art. © 2023 The Authors. Published by Elsevier B.V.

关键词： Industry 4.0

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