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A New Model-Based Dead-Time Compensation Strategy for Cascaded H-Bridge Converters

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第4期70卷 3793-3802页

作者： Li, Baojin Xu, Jinbang Ye, Jie Wang, Haozhe Huang, Songtao Li, Yesong Shen, Anwen Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Natl Key Lab Sci & Technol Multispectral Informat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

Cascaded H-bridge multilevel converter can generate high-voltage and high-power output with low harmonics. However, the error voltage caused by dead-time effect will distort the output waveform, which depends on the phase current polarity. Since the normal dead-time compensation method based on current sampling is often disturbed by sampling error and transmission delay, a novel current prediction method is proposed for dead-time compensation of cascaded H-bridge converter in this article. This method, based on phase-shift carrier pulsewidth modulation, reconstructs the switch pattern, and combined with the system model, can easily predict the phase currents. Excellent compensation performance can be obtained by dead-time compensation according to the predicted current. Simulation and experiments are built to validate the excellent performance of the proposed method applied to cascaded H-bridge converters.

关键词： Cascaded H-bridge (CHB) current prediction dead-time multilevel converter phase-shift carrier pulsewidth modulation (PSC-PWM)

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Fully Connected Neural Network-Based Fixed-Time Adaptive Sliding Mode control for Fuzzy Semi-Markov System

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第10期20卷 12317-12327页

作者： Ren, Fangmin Wang, Xiaoping Li, Yangmin Zeng, Zhigang Educ Minist China Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Brain Inspired Intelligent Syst Wuhan 430074 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong 999077 Peoples R China

This article mainly explores the fixed-time control problem of fuzzy semi-Markov systems with uncertainties and unknown transition rates. Firstly, the T-S fuzzy semi-Markov system is established by using the membership relation of fuzzy logic and Markov probability property. Then, unlike the existing fixed-time control strategies, this work uses a hyperbolic sine function to replace the traditional multiple powers fixed-time control method and construct a novel fixed-time adaptive integral sliding mode control strategy, which reduces the complexity of the controller and adaptive law while optimizing the sliding mode surface and improving the fixed-time convergence performance of the system. Moreover, compared with current methods that require the assumption that the unknown function satisfies the Lipschitz condition or is bounded, the fully connected neural network is introduced to approximate the unknown nonlinear function in the system, improving the intelligence and practicality of the controller. Finally, the theoretical results are verified through numerical simulation, showing the superior performance of achieving fixed-time stability through the proposed control scheme, the gap in the study of fixed-time control using hyperbolic sine functions and fully connected neural networks is filled.

关键词： Stability criteria Convergence Adaptive systems Uncertainty Asymptotic stability Thermal stability Informatics Adaptive integral sliding mode control (SMC) fixed-time stability fully connected neural network fuzzy semi-Markov system

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ERNetCL: A novel emotion recognition network in textual conversation based on curriculum learning strategy

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KNOWLEDGE-BASED SYSTEMS 2024年 286卷

作者： Li, Jiang Wang, Xiaoping Liu, Yingjian Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Inst Artificial Intelligence Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Brain inspired Intelligent Syst Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China

Emotion recognition in conversation (ERC) has emerged as a research hotspot in domains such as conversational robots and question-answer systems. How to efficiently and adequately retrieve contextual emotional cues has been one of the key challenges in the ERC task. Existing efforts do not fully model the context and employ complex network structures, resulting in limited performance gains. In this paper, we propose a novel emotion recognition network based on curriculum learning strategy (ERNetCL). The proposed ERNetCL primarily consists of temporal encoder (TE), spatial encoder (SE), and curriculum learning (CL) loss. We utilize TE and SE to combine the strengths of previous methods in a simplistic manner to efficiently capture temporal and spatial contextual information in the conversation. To ease the harmful influence resulting from emotion shift and simulate the way humans learn curriculum from easy to hard, we apply the idea of CL to the ERC task to progressively optimize the network parameters. At the beginning of training, we assign lower learning weights to difficult samples. As the epoch increases, the learning weights for these samples are gradually raised. Extensive experiments on four datasets exhibit that our proposed method is effective and dramatically beats other baseline models.

关键词： Emotion recognition in conversation Contextual modeling Curriculum learning Neural network

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Producing Considerate Responses: Progressive Staged Training for Emotional Support Conversation

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2024年

作者： Lv, Guoqing Li, Jiang Wang, Xiaoping Zhan, Xin Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Inst Artificial Intelligence Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Brain Inspired Intelligent Syst Wuhan Chin Myanmar Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China

Emotional support conversation (ESC) aims to alleviate the negative emotions of help-seekers by providing psychological assistance. Existing approaches typically overlook the abundant annotations contained in the ESC dataset, such as the situation descriptions and feedback scores of seekers, which limits their performance. In an effort to utilize the annotation information to enhance the emotional support ability of the backbone, we propose a three-stage training method called BlenderBot-ThTra for ESC systems. The proposed BlenderBot- ThTra involves the following three training processes: fine-tuning with supplemental feedback utterance, fine-tuning with auxiliary situation restoration, and calibration with the helpfulness estimation. The first stage aims to intensify the backbone's perception of conversational context, the second stage propels the backbone into excavating the causes of the emotional distress faced by the seeker. In the third stage, we leverage a Bayesian method based on the seeker's feedback scores to train a helpfulness evaluation model, then exploit a contrastive learning method to calibrate the ESC backbone. We conduct experiments on the standard multiturn ESC dataset, and the results demonstrate that BlenderBot-ThTra has a significant advantage in generating more supportive and adaptive responses.

关键词： Training Emotion recognition History Contrastive learning Bayes methods Semantics Predictive models Measurement Evaluation models Data models Dialog generation dialog system emotional support conversation (ESC) multistage learning

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A remaining useful life prediction method of aluminum electrolytic capacitor based on wiener process and similarity measurement

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MICROELECTRONICS RELIABILITY 2023年第1期142卷

作者： Zhao, Jin Zhou, Yang Zhu, Qi Song, Yujin Liu, Yang Luo, Hui Huazhong Univ Sci & Technol Key Lab Image Informat Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Wuhan 430074 Peoples R China

Complex characteristics such as non-linearity and multi-stage are usually presented during the degradation process of aluminum electrolytic capacitors (AECs). Therefore, it is difficult to accurately predict the capacitors' remaining useful life (RUL), which is significant to the system's reliability. Based on the model of Wiener process with linear drift, a simple two-stage RUL predicting method for AECs is proposed in this paper. In the offline stage, the Box-Cox transformation (BCT) is first utilized to linearize the degraded data. Then the model parameters of BCT are identified, and the Shapiro-Wilk test is employed to verify whether the transformed data meet the linearity. In the online stage, based on similarity measurement, the drift coefficient of the Wiener process is updated in real-time. By combining BCT and similarity measurement, the nonlinear and multi-stage problems are effectively solved. Finally, the proposed method is verified on NASA's accelerated degradation data set. Experimental results show that the proposed method can automatically learn the capacitor's complex degradation characteristics and accurately predict its RUL.

关键词： Aluminum electrolytic capacitors Remaining useful life prediction Wiener process Box-Cox transformation Similarity measurement

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USV Path Planning Based on ACO-SA Algorithm 42

USV Path Planning Based on ACO-SA Algorithm

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42nd Chinese control Conference, CCC 2023

作者： Luo, Chuanshang Tang, Yifeng Huang, Zhihui Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper solves USV path planning problem constrained by multiple factors via ant-colony optimization algorithm. First, this paper uses the ways of multi-objective optimization to model the USV path planning problem. An improved ant colony algorithm named ACO-SA is put forward afterwards to effectively solve the problem. The algorithm is a combination of ACO algorithm(ant colony algorithm) and SA algorithm(simulated annealing algorithm), which has three improments: change the initial distribution of pheromone to guide the search when the algorithm has just started running;change the heuristic function and state transition probability taking three factors into consideration;change the pheromone update rule and make the ants compete for the right to update pheromone by simulated annealing algorithm, and update the best solution by the same algorithm. Finally, simulation experiment and field experiment are conducted to check the validity of ACO-SA algorithm. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Simulated annealing

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Dynamic Vertical Peer-to-Peer Carbon Right Sharing Management for Microgrid Clusters With Multiple Structural Demand Response

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年

作者： Zhou, Wei Lai, Jingang Li, Xi Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China

Carbon trading mechanisms can constrain carbon emissions in energy supply, while demand response (DR) mechanisms have the potential to achieve low-carbon oriented energy consumption. Based on these, this paper focuses on mechanism-driven deep decarbonization methods of microgrid clusters (MGCs) from both source and load sides, and the key contributions are threefold. First, a novel dynamic vertical peer-to-peer carbon trading framework is proposed with profitability and fairness, in which a dynamic internal carbon emission right (CER) pricing mechanism is designed based on the supply-demand ratio of CERs and trading prices of the external primary carbon market. Then, a multiple structural DR mechanism is developed to increase the on-site utilization of renewable energy and decrease carbon emissions of MGCs, which considers the influence of electricity prices, the matching degree between renewable energy and loads, and these psychological preferences of users. Moreover, a DR feedback correction strategy is proposed to address the volatility of DR results caused by changes in load elasticity. Numerical results show that the proposed method can reduce carbon emissions by more than 15% without increasing the economic burden, which validates the effectiveness in improving the economic and low-carbon performance of MGCs' operation.

关键词： Carbon dioxide Elasticity Renewable energy sources Psychology Load modeling Economics Peer-to-peer computing Biological system modeling Emissions trading Electricity Feedback correction microgrid clusters (MGCs) multiple structural demand response (MSDR) peer-to-peer (P2P) carbon trading

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Exponential Consensus of Multiagent Systems Based on Nonlinear Parabolic PDEs via Intermittent Boundary control

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2023年第8期53卷 4833-4842页

作者： Qiu, Qian Su, Housheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China

The exponential consensus issue is investigated for leader-following multiagent systems (MASs) based on nonlinear parabolic partial differential equations (PDEs) on a directed graph via intermittent boundary control (IBC) methods. On the one hand, when the system's state is accessible, an IBC protocol is designed based on the transfer information generated by the agent's communication with its neighbors and the information coupling at the boundary x = l, and the sufficient conditions for exponential consensus of leader-following MASs are obtained. On the other hand, when the system's state is not available completely, the agent's state is estimated by the proposed observer, and the observer's coupling information and the boundary coupling information of the agent are adopted to design an IBC protocol to solve the leader-following consensus issue. Finally, two numerical simulations are supplied to account for the obtained theoretical results.

关键词： Exponential consensus intermittent boundary control (IBC) leader-following multiagent systems (MASs) nonlinear parabolic partial differential equations (PDEs) observer

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Fully Distributed Model-Free Flocking of Multiple Euler-Lagrange Systems

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION processing OVER NETWORKS 2024年 10卷 565-573页

作者： Long, Mingkang Chen, Yin Su, Housheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China Univ Strathclyde Dept Elect & Elect Engn Glasgow City G1 1XW Scotland

In this paper, we investigate the leader-follower flocking issue of multiple Euler-Lagrange systems (MELSs) with time-varying input disturbances and completely unknown model parameter information under a proximity graph. Particularly, each follower can only access information from other agents that the relative distance between them is not greater than communication distance. Firstly, based on adaptive control theory, we propose a model-free leader-follower flocking algorithm with constant coupling gains, that is the controller design does not require any dynamic parameter information. Then, for fully distributed design (i.e. no requirement for any global information of the communication graph), edge-based adaptive coupling gains are applied for the above algorithm. The leader-follower flocking of MELSs can be achieved by all proposed algorithms under a connected and no-collision initial proximity graph. Finally, we show some simulation results to illustrate the effectiveness of all proposed flocking algorithms.

关键词： Heuristic algorithms Topology Adaptation models Vectors Information processing Collision avoidance System dynamics Flocking multiple euler-lagrange systems robust control model-free fully distributed

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When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo

When Epipolar Constraint Meets Non-local Operators in Multi-...

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IEEE/CVF International Conference on Computer Vision (ICCV)

作者： Liu, Tianqi Ye, Xinyi Zhao, Weiyue Pan, Zhiyu Shi, Min Cao, Zhiguo Huazhong Univ Sci & Technol Minist Educ Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)9798350307184

Learning-based multi-view stereo (MVS) method heavily relies on feature matching, which requires distinctive and descriptive representations. An effective solution is to apply non-local feature aggregation, e.g., Transformer. Albeit useful, these techniques introduce heavy computation overheads for MVS. Each pixel densely attends to the whole image. In contrast, we propose to constrain non-local feature augmentation within a pair of lines: each point only attends the corresponding pair of epipolar lines. Our idea takes inspiration from the classic epipolar geometry, which shows that one point with different depth hypotheses will be projected to the epipolar line on the other view. This constraint reduces the 2D search space into the epipolar line in stereo matching. Similarly, this suggests that the matching of MVS is to distinguish a series of points lying on the same line. Inspired by this point-to-line search, we devise a line-to-point non-local augmentation strategy. We first devise an optimized searching algorithm to split the 2D feature maps into epipolar line pairs. Then, an Epipolar Transformer (ET) performs non-local feature augmentation among epipolar line pairs. We incorporate the ET into a learning-based MVS baseline, named ET-MVSNet. ET-MVSNet achieves state-of-the-art reconstruction performance on both the DTU and Tanks-and-Temples benchmark with high efficiency. Code is available at https://***/TQTQliu/ET-MVSNet.

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