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2023 Jiangsu Annual Conference on Automation, JACA 2023

作者： Li, Weitai Lu, Xiaobo Cao, Yichao School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781839539848

Smoke is a distinctive feature of pre-fire combustion and it is critical to prevent fires by detecting smoke. Previous work has demonstrated that deep learning methods have a wide range of applications in the field of smoke detection. However, existing methods still have some problems, i.e., it is difficult to balance the relationship between accuracy and speed. In order to solve the existing problems, we proposed Efficient Temporal Alignment Network (ETAN) for Video Smoke Detection. Feature Aggregation Module (FAM) was designed to extract the dynamic features between frames, and we proposed Recursive Memory Feature Update (RMFU) module to maintain the features of past frames and fuse the current features to boost detection performance. Finally, experiments demonstrated that the proposed method improved about 3.8 mAP compared with base detector with little increase in the number of parameters, and outperformed all the single-frame detection methods with the same amount of parameters. Compared with video smoke detection methods, the detection achieved close to the same accuracy while 6.1 times faster than multi-frame methods. © The Institution of Engineering & Technology 2023.

关键词： Smoke

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Adaptive control for Stochastic Nonlinear systems with Input Saturation Based on Multi-dimensional Taylor Network 20

Adaptive Control for Stochastic Nonlinear Systems with Input...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Zheng, Xiao-Yi Yan, Hong-Sen Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University School of Automation Nanjing210096 China

ISBN: (纸本)9798350320831

For stochastic nonlinear systems with input saturation, few of the existing control methods use a suitable auxiliary system to solve input saturation problem, and most of them are for deterministic systems. In this study, according to the backstepping approach and the Lyapunov stability theorem, utilizing multi-dimensional Taylor network (MTN), an adaptive controller is presented to secure that all closed-loop signals keep bounded in probability, in which MTN is implemented to approach the uncertain function during the controller design. Moreover, the impact raised by input saturation is mitigated by designing an appropriate auxiliary system, in which the order of the auxiliary system is the same as that of the controlled system. Furthermore, unlike the majority of prior findings, the final output signal could be constrained in a mean quartic sense by an explicit expression of the input saturation error (the difference between the control signal and the saturation input) and the parameters used for design. Finally, the efficiency of the suggested control methodology is confirmed by providing an example. © 2023 IEEE.

关键词： Stochastic systems

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LSTM-TD3-based control for delayed drone combat strategies 19th

LSTM-TD3-based control for delayed drone combat strategies

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19th Chinese Intelligent systems Conference, CISC 2023

作者： Ji, Bingyu Wang, Jun Zhang, Hailin Zhang, Ya School of Automation Southeast University Nanjing210096 China Key Laboratory Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9789819968817

Reinforcement learning has made great achievements in the field of game confrontation, and military rendition intelligence is also imminent. In this paper, we propose a game confrontation game model based on LSTM and deep reinforcement learning for the red and blue sides of the drones in the delayed *** action buffer pair is added to the original battlefield environment to create a large latency environment, a TD3 algorithm is designed to join LSTM to predict the state trend, and a historical data pool is built using PER. The training results in the simulation platform show that the model has a significant improvement in effectiveness in the large latency environment, with a 0.22 improvement in battle damage ratio and a 34.76% improvement in win rate over the original model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Reinforcement learning

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Non-Smooth Speed control of Switched Reluctance Motor Based on Generalized Proportional Integral Observer 42

Non-Smooth Speed Control of Switched Reluctance Motor Based ...

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42nd Chinese control Conference, CCC 2023

作者： Yin, Qingzhao Tian, Zheng Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9789887581543

This paper investigates the speed regulation control of switched reluctance motor (SRM) systems. To improve the antidisturbance performance of SRM, a composite non-smooth control strategy is proposed. First, the structure of SRM is analyzed, and a simplified nonlinear model is obtained based on a segmented representation of the varying phase inductance. A virtual control function is introduced to represent the nonlinear part of the torque equation, whose inverse function is cascaded to linearized the nonlinear model. Second, a generalized proportional integral observer (GPIO) is constructed to estimate the lumped disturbance of the system, which is used for feedforward compensation design. Finally, a composite speed controller is designed based on a combination of finite time proportional feedback and feed-forward compensation based on GPIO (FTP+GPIO). The speed error closed-loop system can be regarded as a first-order finite time control system with bounded disturbances. Strict analysis shows that the proposed scheme can improve the anti-disturbance performance of the closed-loop system. The effectiveness of the proposed method is verified by simulation results. Moreover, it is compared with proportional feedback combining feed-forward compensation (P+GPIO) method and proportional integral (PI) control method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Closed loop systems

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Person Re-identification Based on Dual-channel Attention and Local Feature Fusion

Person Re-identification Based on Dual-channel Attention and...

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2022 International Conference on Electrical, control and Information Technology, ECITech 2022

作者： Ning, Xinkuang Shao, Jiayu Lin, Wenjie Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9783800759170

Aiming at improving low accuracy of existing person re-identification algorithms in dealing with low image resolution, different illumination, diverse poses, and viewing angles, this paper proposes a person re-id algorithm based on dual-channel attention and local feature fusion. After ResNet50, it is followed by the spatial attention and the channel attention to extract the global features. Then the feature map segmentation is performed to extract the local features, and a fusion feature with strong judgment is obtained. In addition, this paper adds the central loss constraint item to the triplet hard loss. The triplet_center loss joint cross-entropy loss function further to improve adaptability of the model in complex scenarios. The proposed method is compared and tested on the CUHK03, DukeMTMC-reID and Market-1501 data sets, and the accuracy of Rank-1 reached 96.1%, 89.8% and 79.8%. This algorithm makes full use of the features of different depths and the key information of interest. The module has a solid discriminative ability. Also the accuracy of mean average precision of the proposed method is better than other advanced algorithms. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Image resolution

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Transformer-Based Scenario Generation of Multi-segment Monotonic Increasing Bidding Curves of Power Plants

Transformer-Based Scenario Generation of Multi-segment Monot...

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International Conference of Electrical, Electronic and Networked Energy systems, EENES 2024

作者： Xie, Haochuan Lv, Jianhu Wang, Ying Yuan, Kun College of Software Southeast University Suzhou China China Electric Power Research Institute Beijing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9789819618637

With the relaxation of electricity market regulation, power plants are permitted to engage in bidding. The bidding outcomes in the competitive market differ significantly from those in the previously regulated market. These differences in bidding outcomes will further impact power flow and system security. To provide a reference for practical electricity market operations, make market simulation more realistic, it is crucial to analyze and establish a model to simulate the bidding behavior of power generators. This paper applies Transformer networks to predict multi-segment bidding behaviors of power plants, we have improved the classic Transformer network by adopting a one encoder-two decoder format, considering six key factors influencing bidding behavior: unit ID, fuel type, capacity, location, system load, and load ratio. Additionally, monotonicity of the multi-segment bidding curves of power plants is taken into account, and monotonicity loss functions are introduced to achieve this goal. We apply this method to predict bidding behaviors in power plants in the Australian electricity market, validating the accuracy of the model. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： bidding curves generation monotonicity constraint power market Transformer-based

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Image-Based Fast Finite-Time Target Tracking control of Onboard Inertially Stabilized Camera Platform

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IEEE Transactions on Industrial Electronics 2024年第12期71卷 16409-16418页

作者： Sun, Xunhong Zhu, Wenwu Du, Haibo Chen, Weile Chen, Chih-Chiang Hefei University of Technology School of Electrical Engineering and Automation Hefei230009 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University School of Automation Nanjing210096 China National Cheng Kung University Department of Systems and Naval Mechatronic Engineering Tainan70101 Taiwan

In this article, we investigate the problem of fast finite-time target tracking control of the inertially stabilized platform (ISP) with a camera that mounted on a mobile robot. At first, the kinematics of the onboard ISP target tracking system is established by the geographic coordinate and pinhole camera model, which includes the state-dependent uncertainties and external disturbances. Then, based on the image information captured by camera, a continuous image-based fast finite-time control algorithm is designed for target tracking. Rigorous analysis proves that the target can be tracked at the center of camera's view in finite time in the absence of disturbances. In the presence of disturbances, the tracking error can converge to a region around the origin in finite time. Simulation and experimental comparisons are presented to confirm the efficiency of the proposed method. © 1982-2012 IEEE.

关键词： Mobile robots

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Distributed Asymptotic Consensus in Directed Networks of Nonaffine systems With Nonvanishing Disturbance

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1133-1140页

作者： Qingling Wang Changyin Sun School of Automation Southeast UniversityNanjing 210096 Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096China

In this paper the distributed asymptotic consensus problem is addressed for a group of high-order nonaffine agents with uncertain dynamics,nonvanishing disturbances and unknown control directions under directed networks.A class of auxiliary variables are first introduced which forms second-order filters and induces all measurable signals of agents’*** view of this property,a distributed robust integral of the sign of the error(DRISE)design combined with the Nussbaum-type function is presented that guarantees not only the desired asymptotic consensus,but also the uniform boundedness of all closed-loop *** with the traditional sliding mode control(SMC)technique,the main feature of our approach is that the integral operation in the proposed control algorithm is designed to be adopted in a continuous manner and ensures less chattering *** results for a group of Duffing-Holmes chaotic systems are employed to verify our theoretical analysis.

关键词： Asymptotic consensus nonaffine systems nonvanishing disturbance Nussbaum-type functions unknown control directions

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Adaptive Augmented Kalman Filter-Based control for Electronic Throttle systems with Disturbances and Noises 42

Adaptive Augmented Kalman Filter-Based Control for Electroni...

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42nd Chinese control Conference, CCC 2023

作者： Li, Wen Su, Jinya Li, Shihua School of Automation Southeast University Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing210096 China

ISBN: (纸本)9789887581543

In this study, we investigate the control problem of electronic throttle systems in the presence of practical challenges such as disturbances and measurement noises. To address these challenges, we propose an adaptive augmented Kalman filter (AAKF) based control approach that combines the strengths of extended state observer in disturbance estimation and adaptive Kalman fil-ter in adaptive noise filtering. The outputs of AAKF are integrated into the Backstepping control design, resulting in a composite control that concurrently achieves fast disturbance rejection and noise suppression. We conduct a comparative simulation study against conventional methods without adaptive filtering to validate the effectiveness of the proposed AAKF-based control strat-egy, which exhibits superior position control accuracy and disturbance attenuation performance. We envision that our proposed control strategy will contribute to improving vehicle power, fuel economy, and emission performance. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Adaptive filtering

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Fixed-Time Adaptive Tracking Event-Based control for Uncertain Stochastic Nonlinear systems With Output Constraints

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International Journal of Robust and Nonlinear control 2025年第0期

作者： Wang, Kun Xie, Liping Yuan, Yixuan Zhang, Kanjian Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China

This paper focuses on an adaptive fixed-time tracking control problem for nonstrict-feedback stochastic nonlinear systems with unknown control coefficients and output constraints. To overcome this problem, this article introduces a unified system transformation function to facilitate the transition of the system from constrained to unconstrained states. Subsequently, a fuzzy approximation principle is utilized for handling unknown terms in the transformed system, while Nussbaum functions are employed to manage unknown control directions. Then, combined with the backstepping technique, an adaptive fixed-time tracking controller is designed with an event-triggered mechanism, which not only achieves the convergence of tracking errors within a limited time independent of initial states, but also conserves resources. Under the proposed tracking controller, practical fixed-time stability can be ensured for the closed-loop system. Finally, two simulation examples demonstrate the efficacy of the proposed scheme. © 2025 John Wiley & Sons Ltd.

关键词： Stochastic systems

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