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31st Youth Academic Annual Conference of Chinese Association of Automation, YAC 2016

作者： Wang, Pan Chai, Lin Fei, Shumin School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

ISBN: (纸本)9781509044238

This thesis researches the problem of global stabilization via output feedback by using linear sampled data controller for a family of nonlinear time-delay systems which satisfy a linear growth condition. Firstly, an inductive approach is proposed to estimate the state growth in nonlinear time-delay systems. Secondly, in the condition of just the output is measurable, a linear sampled data controller via output feedback with a scaling gain is designed by means of output domination method. Finally, the scaling gain which is a positive constant and a appropriate sampling period are determined to stabilize the closed-loop system asymptotically. © 2016 IEEE.

关键词： Closed loop systems

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Feature fusion methods for robust speech emotion recognition based on deep belief networks 16

Feature fusion methods for robust speech emotion recognition...

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5th International Conference on Network, Communication and Computing, ICNCC 2016

作者： Wu, Ao Huang, Yongming Zhang, Guobao Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781450347938

The speech emotion recognition accuracy of prosody feature and voice quality feature declines with the decrease of SNR (Signal to Noise Ratio) of speech signals. In this paper, we propose novel sub-band spectral centroid weighted wavelet packet cepstral coefficients (W-WPCC) for robust speech emotion recognition. The W-WPCC feature is computed by combining the sub-band energies with sub-band spectral centroids via a weighting scheme to generate noise-robust acoustic features. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre-trained layer by layer and then fine-tuned using back propagation algorithm. The welltrained deep neural networks are capable of modeling complex and non-linear features of input training data and can better predict the probability distribution over classification labels. We extracted prosody feature, voice quality features and wavelet packet cepstral coefficients (WPCC) from the speech signals to combine with W-WPCC and fused them by Deep Belief Networks (DBNs). Experimental results on Berlin emotional speech database show that the proposed fused feature with W-WPCC is more suitable in speech emotion recognition under noisy conditions than other acoustics features and proposed DBNs feature learning structure combined with W-WPCC improve emotion recognition performance over the conventional emotion recognition method. © 2016 ACM.

关键词： Emotion Recognition

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Adaptive Multi-Dimensional Taylor Network Tracking control for Stochastic Nonlinear systems with Full-State Constraints and Input Saturation 8

Adaptive Multi-Dimensional Taylor Network Tracking Control f...

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8th International Conference on Robotics and Automation engineering, ICRAE 2023

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

ISBN: (纸本)9798350327656

In this study, an adaptive tracking controller using multi-dimensional Taylor network (MTN) is presented for state-constrained nonlinear stochastic systems with saturated input, in which MTN is implemented to model the unknown nonlinear functions. Firstly, the barrier Lyapunov function (BLF) and backstepping technique are combined under a unified framework to eliminate the impact of full-state constraints. Then, the effect raised by saturated input is solved by introducing an appropriate auxiliary system. Furthermore, by employing the Lyapunov stability theorem, the designed adaptive controller could ensure that all closed-loop signals are bounded in probability, the output signal can track the desired signal successfully, the tracking error is bounded by the expected bound, and the system state constraints are never violated. Finally, the efficiency of the suggested control methodology is confirmed by providing an example. © 2023 IEEE.

关键词： Lyapunov functions

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HarmonyNav: Robot Navigation in Human-Robot Coexistence Environment Considering Group and Pedestrian Intentions

HarmonyNav: Robot Navigation in Human-Robot Coexistence Envi...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Wang, Yutao Fang, Fang Liu, Chenyang Fan, Tao Li, Yi The Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

Service robots must navigate efficiently and harmoniously in human-robot coexistence environments. Previous studies often treated pedestrians as independent entities, ignoring human intentions and leading to group intersections and performance issues. We introduce HarmonyNav, a crowd navigation algorithm that enhances human-robot harmony. Our method uses Human-Robot Interaction sub-networks to account for indirect group impacts on pedestrians and predicts pedestrian trajectories to infer intentions. Employing proximal policy optimization (PPO) in reinforcement learning, we develop a harmonious navigation policy. In simulation experiments, our results show improved navigation performance, reducing group intersections and individual intrusions. © The Institution of engineering & Technology 2024.

关键词： Reinforcement learning

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A nested constraints based anti-disturbance collision-free formation control scheme for multi-mobile robot systems

A nested constraints based anti-disturbance collision-free f...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Guodong Wang, Xiangyu Li, Shihua Niu, Dan Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China

ISBN: (纸本)9781665465335

This paper investigates distributed formation control of multi-mobile robot systems with collision avoidance. A novel nested constraints based anti-disturbance formation control scheme is established, which contains two parts. In the first part, a formation signal generator is constructed on the communication network by using proper distributed cooperative control approaches and artificial potential field-based methods, such that it "completes"the desired formation control task in its outputs. In the second part, by combining proper disturbance estimations, some nonlinear tracking controllers are designed for the robots to track the corresponding outputs of the generator asymptotically. A "nested constraint mechanism"is put forward accordingly and applied to limit the generator's outputs and the robots' tracking errors. In this way, the studied multi-mobile robot systems realize the formation control goal with collision avoidance. Compared with existing results, the proposed method has a better plug-and-play feature to deal with the tight encapsulations of the practical robot products, and has better convergence performances with the existence of disturbances. Some experiments are given to validate the effects of the proposed methods. © 2022 IEEE.

关键词： Collision avoidance

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An Adaptive Event-Triggered Secondary Regulation Strategy for Microgrids with Loss of Effectiveness Actuator Faults 49

An Adaptive Event-Triggered Secondary Regulation Strategy fo...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Qiu, Xuechao Wang, Xiangyu Niu, Dan Wang, Xiangyu School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350331820

In this paper, an adaptive event-triggered secondary regulation strategy is investigated for microgrids with loss of effectiveness actuator faults. In order to deal with unknown loss of effectiveness actuator faults, a distributed secondary regulation strategy is proposed, which achieves voltage and frequency regulations, as well as power sharing. Meanwhile, to save system resources and relieve the communication burden, an adaptive event-triggered mechanism is designed. Finally, some simulation results are given to validate the proposed strategy, which indicates that the proposed strategy reduces the controller updates and increases the reliability of system. © 2023 IEEE.

关键词： Actuators

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Fault detection method of photovoltaic system based on power change of array 4

Fault detection method of photovoltaic system based on power...

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4th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2021

作者： Tan, Chao Li, Chenxi Zhang, Kanjian Wei, Haikun Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781450385053

The fault detection of photovoltaic power generation system is of great significance in photovoltaic plant management. The conventional fault detection method of photovoltaic power system requires additional sensors, and the fault detection scheme needs to be redesigned if the parameters of the photovoltaic plant change. Therefore, for large photovoltaic plants, it is necessary to develop a method that does not require the use of external sensors or the detailed parameters of the photovoltaic plant. This paper proposes a photovoltaic system fault detection method based on photovoltaic array current and voltage data. This method does not require additional sensor data such as irradiance and temperature. The failure of photovoltaic system can be detected through the change of power, and the abnormal situation of photovoltaic power station can still be detected under cloudy and shaded conditions. The advantages of this method are that there is no need for complex and diverse sensor equipment, the calculation is simple and the fault detection ability is accurate. The experimental data of Padang Poverty Power Station of State Grid has been verified. © 2021 ACM.

关键词： Fault detection

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Transformer Based Multi-modal Fusion For Place Recognition with Self-attention Mechanism

Transformer Based Multi-modal Fusion For Place Recognition w...

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2022 Chinese Automation Congress, CAC 2022

作者： Pan, Yan Yu, Xiang Chang, Zeqing Fang, Fang Zhou, Bo School of Automation Southeast University Ministry of Education The Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China

ISBN: (纸本)9781665465335

Autonomous driving still leaves a challenging task that how to apply the complementary information captured from different sensors, i.e. cameras and LiDAR, to handle place recognition task. In this paper, a brand new pipeline was designed to tackle the retrieval problem with a multi-modal late fusion. The light-weighted convolutional blocks is applied to encode features from images, followed by converting them into pseudo point clouds. Inspired by the progress of the Transformer, the network employs a residual point transformer module to extract feature vectors for 3D points and pseudo point clouds respectively. Finally, the two corresponding local descriptors are fused to get a robust fused global descriptor, which is capable of place recognition task after end-to-end training. Experimental results collected from sequence 00, 02, 05, 06 of KITTI dataset validate that fusing information from two modalities is able to enhance performance. © 2022 IEEE.

关键词： Autonomous vehicles

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食品系统与气候变化、空气污染之间的相互作用综述（英文）

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engineering 2025年第1期 215-233页

作者： Chaopeng Hong Rui Zhong Mengyao Xu Peidong He Huibin Mo Yue Qin Danna Shi Xinlei Chen Kebin He Qiang Zhang Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and Ecology Shenzhen International Graduate School Tsinghua University State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex College of Environmental Sciences and Engineering Peking University Institute of Data and Information Shenzhen International Graduate School Tsinghua University State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University

Food systems are deeply affected by climate change and air pollution, while being key contributors to these environmental challenges. Understanding the complex interactions among food systems, climate change, and air pollution is crucial for mitigating climate change, improving air quality, and promoting the sustainable development of food systems. However, the literature lacks a comprehensive review of these interactions, particularly in the current phase of rapid development in the field. To address this gap, this study systematically reviews recent research on the impacts of climate change and air pollution on food systems, as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution. In addition, this study summarizes various strategies for mitigation and adaptation, including adjustments in agricultural practices and food supply chains. Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions. This review offers a critical overview of current research on the interactions among food systems, climate change, and air pollution and highlights future research directions to support the transition to sustainable food systems.

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Fault-Tolerant Cooperative Motion Planning of Connected and Automated Vehicles at a Signal-Free and Lane-Free Intersection

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IFAC-PapersOnLine 2018年第24期51卷 60-67页

作者： Li, Bai Zhang, Youmin Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Canada

Compared with a conventional intersection, a signal-free and lane-free intersection enables the vehicles to drive more flexibly, thereby to promote the throughput and to reduce congestions. This work proposes a fault-tolerant cooperative motion planning method for a number of connected and automated vehicles (CAVs) which are passing through a signal-free and lane-free intersection. Partial loss of actuator effectiveness is considered as the fault type. Even a subtle fault may significantly affect the overall team performance. Thus correctly judging whether each faulty/healthy CAV can still achieve its original goal is impossible until a corresponding motion replanning problem turns out to be solvable or not. To maximize the completeness of the original task, we propose a parallel computation framework, wherein the fault-recovery motion replanning problems in multiple levels of task completeness are tried simultaneously. Concretely, i) each faulty/healthy CAV should accomplish its original goal; ii) only each healthy CAV is required to accomplish its original goal; and iii) all the faulty/healthy CAVs try to stop safely without the need to achieve any original goals. Problems iii), ii), and i) are ranking with increasing computational difficulty. Among all the three problems, the achievable solution to the most difficult one is implemented as the fault-recovery strategy. © 2018

关键词： Motion planning Automation Fault tolerance Vehicles Automated vehicles Co operative control connected Intersection managements Optimal controls

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