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2023 Seminar on Information Computing and Processing, ICP 2023

作者： Protasov, Yakov A. Erofeev, Dmitry A. Borovkov, Grigoriy S. Novozhilov, Igor M. Saint Petersburg Mining University Department of 'System Analysis and Control' Saint Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Department of Automation and Control Processes Saint Petersburg Russia

ISBN: (纸本)9798350369830

This article offers a solution to the problem of optimizing the time-resource ratio using neural network algorithms and a multidimensional knapsack. By implementing the knapsack sorting, optimal time and energy activities are selected, and the neural network fills in the free intervals based on the entered parameters. The ultimate goal of the «Scheduling automation system» is to increase efficiency, reduce energy consumption of the final user. © 2023 IEEE.

关键词： automation

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Motor Fault Diagnosis Under Complex Working Conditions Based on Signal Fusion and CA-CNN

Motor Fault Diagnosis Under Complex Working Conditions Based...

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2024 China automation Congress, CAC 2024

作者： Cai, Mingxuan Liu, Qi Liu, Yuxiang Yang, Bo Department of Automation Shanghai Jiao Tong University shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350368604

Accurate fault diagnosis plays a key role in the safe and efficient operation of electrical motors. Aiming at multi-class motor fault diagnosis under complex working conditions, a signal fusion-based fault diagnosis framework is proposed. Measurement parameters from different sensors are first transformed by wavelet denoising and fast Fourier transform (FFT). Then, multiple parameters spectrum and working condition information are integrated and converted into high-dimension matrices. Finally, a channel-attention-based convolution neural network (CA-CNN) is proposed to extract fault patterns from a reconstructed matrix and output diagnosis results. Experiment results on both simulated and experimental datasets verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Convolutional neural networks

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NeFF: Semantic Information Learning In 3D Space Using Neural Feature Field

NeFF: Semantic Information Learning In 3D Space Using Neural...

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2024 China automation Congress, CAC 2024

作者： Yang, Yimu Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368604

Inferring a 3D space with partial observation requires prior knowledge from previous experience, and deep learning offers an intuitive solution. Prior knowledge can be categorized into two extremes Global and Local. Global prior uses input image as a clue to retrieve seen intact 3D objects yielding 3D consistent inference with fewer details. In contrast, Local prior takes advantage of closeby views’ overlapping areas and propagates input image cues to their vicinity via geometry transformation directly, producing realistic inferences around the reference views yet inconsistent inferences away from the reference views. We propose Neural feature field, an implicit 3D neural representation that combines the strength of the Global and Local prior. We represent each 3D scene with a latent embedding, then we perform a global scene-level prior to local view-specific feature prior with the neural feature field and volume rendering technique. Our model learns general scene properties across a category. Given a single input image at test time, the scene latent code is acquired via a two-round optimization process. Experiments on the SRN benchmark show that NeFF generalizes well to unseen objects within the same object category and is capable of producing 3D consistent inferences with sharp details from a single observation. © 2024 IEEE.

关键词： 3D reconstruction

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Uncertainty-Aware Reactive control for Signal Temporal Logic with Unknown Obstacles 14

Uncertainty-Aware Reactive Control for Signal Temporal Logic...

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14th Asian control Conference, ASCC 2024

作者： Chen, Chen Li, Shaoyuan Yin, Xiang Shanghai Jiao Tong University Department of Automation Shanghai200240 China The Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9789887581598

In this paper, we investigate the challenge of con-trol synthesis for Signal Temporal Logic (STL) specifications within workspaces harboring unknown obstacles. We consider a sensing-based control setting, where robots are equipped with sensors with a limited sensing range to acquire obstacle locations with prior information. The objective is to synthesize a control strategy that maximize the robustness degree of the STL tasks while simultaneously minimizing the probability of collisions with obstacles during its operation. To address this, we present a receding horizon reactive control framework, tackling the problem by solving an uncertainty-aware optimal planning problem at each time instant. A key aspect of our approach is the avoidance of explicit computation of collision probability. Instead, we transform the uncertainty-aware synthesis problem into a non-probabilistic optimization problem, and the results of which still provide probabilistic guarantees. Simulation results are provided to illustrate the effectiveness of our approach. © 2024 Asian control Association.

关键词： Temporal logic

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Dual-type Hyperspectral Microscopic Imaging system based on Fourier Transform Imaging Spectrometer 15

Dual-type Hyperspectral Microscopic Imaging System based on ...

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15th International Conference on Information Optics and Photonics, CIOP 2024

作者： Wei, Zhanqi Wu, Kaijie Qin, Yuheng Cheng, Hao Gu, Chaochen Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

This article proposes a hyperspectral microscopic imaging system based on Fourier transform interferometer to broaden the spectral range and obtain more types of spectral information under large field of view. Through stage scanning and light sources switching, transmission and fluorescence spectral images can be obtained successively. The system was validated using fibre tissues imaging. The spectral range covers 300-800 nm, and the spectral resolution is approximately 5 nm. It can be effectively applied to pathology and cytogenetics, obtaining morphological and spectral information to study the structure of the object and observe the similarities and differences of components in different positions. © 2024 SPIE.

关键词： Spectral resolution

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Algorithm for Solving Traveling Salesman Problem Based on Self-Organizing Mapping Network

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 463-470页

作者：朱江辉叶航航姚莉秀蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System Ministry of EducationShanghai 200240China Huawei Technologies Co. Ltd.Shanghai 201206China

Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization *** on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter *** paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic *** show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm *** with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.

关键词： traveling salesman problem(TSP) self-organizing mapping(SOM) combinatorial optimization neu-ral network

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Provably Safe Deep Learning-Based Offset-Free Model Predictive control and its Application to Safety-Critical Autonomous Driving 6

Provably Safe Deep Learning-Based Offset-Free Model Predicti...

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6th International Conference on Robotics, control and automation Engineering, RCAE 2023

作者： Wang, Han Li, Longyan Ning, Chao Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai China

ISBN: (纸本)9798350315301

Offset-free model predictive control (MPC) provides a useful means for controlling systems with uncertainties and constraints, but suffers from the heavy computational burden of repeatedly solving an optimization problem in real time. Such computational issue precludes the possibility of its application in systems requiring high realtime requirements, such as autonomous driving system. To address this problem, we develop a provably safe deep learning-based offset-free MPC framework. Based on the nominal offset-free MPC, the proposed MPC not only reserves the ability of disturbance rejection, but also leverages deep neural networks for approximating the explicit MPC solution to greatly reduce online computational time. Furthermore, a gauge map is used to guarantee the satisfaction of safe constraints. The proposed MPC is used in trajectory tracking control for smart autonomous driving. The simulation results show that the proposed MPC is an order of magnitude faster than the nominal offset-free MPC in safety-critical systems. © 2023 IEEE.

关键词： Model predictive control

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Safe Deep Learning-Based Offset-Free MPC for Green Hydrogen Injected PEMFC systems

Safe Deep Learning-Based Offset-Free MPC for Green Hydrogen ...

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2023 China automation Congress, CAC 2023

ISBN: (纸本)9798350303759

Safe and stable operation of a proton exchange membrane fuel cell (PEMFC) system requires stringent control of oxygen excess ratio (OER). However, the OER regulation in PEMFC is challenging due to frequent fluctuations of current, various modeling nonlinearities, constrained manipulated variable, and real-time requirements. Offset-free model predictive control (MPC) provides a useful means for controlling systems with disturbances and constraints, but suffers from the heavy computational burden of repeatedly solving an optimization problem in real time. Such computational issue precludes the possibility of meeting the real-time requirements of PEMFC. In this paper, a PEMFC cathode gas supply model is firstly established. Next, we develop a safe deep learning-based offset-free MPC algorithm. Based on the nominal offset-free MPC, the proposed MPC not only reserves the ability of disturbance rejection, but also leverages deep neural networks for approximating the explicit solution to the MPC problem to greatly reduce online computational time. Furthermore, a gauge map is used to guarantee the satisfaction of safe constraints regarding compressor voltage. The simulation results show that the proposed MPC is an order of magnitude faster than the nominal offset-free MPC. © 2023 IEEE.

关键词： Model predictive control

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Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 70-76页

作者：茅天阳赵文韬王景川陈卫东 Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China

To achieve precise localization,autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile *** is a time-consuming process,and mechanical distortion will cause extrinsic calibration ***,we propose a lidar-visual-inertial odometry,which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic *** the adapted sliding window mechanism,spatial-temporal alignment is performed to manage measurements arriving at different *** nonlinear optimization with online calibration,visual features,cloud features,and inertial measurement unit(IMU)measurements are used to estimate the ego-motion and perform extrinsic *** experiments were carried out on both public datasets and real-world *** indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.

关键词： autonomous vehicles multi-sensor fusion online calibration

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Triggered Mechanism for Strict Feedback systems under Unknown control Directions 14

Triggered Mechanism for Strict Feedback Systems under Unknow...

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14th Asian control Conference, ASCC 2024

作者： Liu, Guilong Wu, Hongda Yang, Yongliang Xie, Wei Zhang, Weidong School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581598

This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the system, thus impacting the system's stability and convergence speed. When the control directions are unknown, it presents a significant challenge in controller design. To tackle this issue, the Nussbaum-type gains are introduced. However, this method increases communication overhead. Hence, an event-triggered mechanism is introduced to alleviate this burden. Additionally, to achieve and maintain desired target states, satisfying control requirements and performance demands, this paper improves the event-triggered mechanism to achieve asymptotic tracking. Finally, the feasibility and effectiveness of the proposed design are validated through a simulation example. © 2024 Asian control Association.

关键词： Feedback

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