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Model-Free Current Predictive control for PMSMs With Ultralocal Model Employing Fixed-Time Observer and Extremum-Seeking Method

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IEEE Transactions on Power Electronics 2025年第8期40卷 10682-10693页

作者： Lin, Xinpo Liu, Jianxing Liu, Zhuang Gao, Yabin Peretti, Luca Wu, Ligang Harbin Institute of Technology Department of Control Science and Engineering Weihai264209 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China KTH Royal Institute of Technology Division of Electric Power and Energy Systems Stockholm10044 Sweden

Conventional model predictive current control of permanent magnet synchronous machines (PMSMs) relies heavily on a precise mathematical model, which may be challenging to obtain in certain cases. To address this issue, this article proposes a model-free predictive current controller for PMSMs. Specifically, the dynamic model of the motor currents is represented using two ultralocal models, which express the derivatives of a controlled output as the sum of an amplified control input and an unknown offset term. All system parameters, nonlinear terms, and unmodeled dynamics are encapsulated into two offset terms. Online estimation of these two offset terms is performed using a second-order fixed-time convergence observer without requiring exact knowledge of the system parameters in advance. In contrast to both the linear extended state observer and the super-twisting observer, the fixed-time observer enhances convergence speed while concurrently sustaining minimal chatting. To get rid of the need for model rated parameters, an extremum-seeking approach is utilized to tune the control gains in the ultralocal model, where the amplitude of the disturbance item in extremum-seeking approach is adaptively attenuated, resulting in effective reduction of the fluctuations of both the control gains and PMSM's currents in steady state. Subsequently, a predictive controller is designed using this ultralocal model. Finally, the effectiveness and advantages of the proposed control scheme are confirmed through experimental results. © 1986-2012 IEEE.

关键词： Permanent magnets

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Foreign Object Debris detection at aerodromes using YOLOv5 27

Foreign Object Debris detection at aerodromes using YOLOv5

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27th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Suder, Jakub Marciniak, Tomasz Poznan University of Technology Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawla II 24 Poznań60-965 Poland

ISBN: (纸本)9788362065486

The latest EASA recommendations from 2024 indicate the possibility of using machine learning techniques in aerodrome monitoring. The aim of the work was to analyze solutions and prepare FOD (Foreign Object Debris) object detection software on aerodromes. In order to implement the issue, a dataset of photos and video recordings for testing algorithms was developed. The dataset consists of 1480 photos showing FOD at aerodromes and photos of the runway itself, according to EASA and FAA recommendations. FOD detection was implemented using a classical, k-means method and effective YOLOv5. © 2024 Division of Signal Processing and Electronic systems, Poznan University of technology (DSPES PUT).

关键词： Video recording

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Camera-based light source localization for precise luminous intensity measurement of airport lamps 27

Camera-based light source localization for precise luminous ...

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27th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Podbucki, Kacper Marciniak, Tomasz Poznan University of Technology Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawla II 24 Poznań60-965 Poland

ISBN: (纸本)9788362065486

Measuring luminous intensity using electronic sensors requires their precise positioning. In the case of mobile measurement platforms, it is important to detect the light source and thus determine the correct direction of movement of the measuring device. This article presents research on a solution for the initial detection of glowing airport lamps based on camera images. The impact of the selection of parameters and image processing methods on the prepared data set was assessed. The histogram filtration method was introduced to improve the effectiveness of airport lamp localization. The proposed solution was investigated in different weather and daytime conditions. The overall accuracy of the proposed solution is more than 90%. © 2024 Division of Signal Processing and Electronic systems, Poznan University of technology (DSPES PUT).

关键词： Image enhancement

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Switching Learning-Based Cooperative control with Its Application to Connected Automated Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Wan, Meng-Ying Yuan, Yun-Peng Xu, Yong Wu, Zheng-Guang School of Automation Beijing Institute of Technology Beijing China Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Most existing model-based cooperative tracking control approaches heavily rely on precise dynamic models and overlook the transient performance, ultimately resulting in the designed controller falling far short of optimal control effectiveness. To address this issue, this paper proposes a novel switching learning algorithm to optimize the optimal formation tracking control in unknown heterogeneous multi-agent systems. Firstly, a distributed observer-based decentralized formation control protocol is proposed to provide the state estimation of the leader, where the estimated leader's state facilitates that each agent maintains formation distance between the leader and the formation process. Secondly, a decentralized control policy is considered and learned by the iterative solution of the Bellman equation to achieve the optimal formation tracking control for each agent. However, the aforementioned obtained results heavily rely on the system dynamics and an initial stabilizing control policy. To relax these limitations, a data-based switching learning algorithm is proposed, and it consists of a model-free matrix updating learning algorithm and a data-based policy iteration algorithm. In contrast to existing algorithms for similar studies, the proposed algorithms eliminate the system model and initial stabilizing requirements, but also ensure the formation control in an optimal control way. Finally, a practical connected automated vehicles example is given to verify the theoretical analysis. IEEE

关键词： Transient analysis

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Communication Signal Enhancement Algorithm in Low SNR and Complicated Environment 3

Communication Signal Enhancement Algorithm in Low SNR and Co...

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3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Tian, Teng Li, Chan Chen, Ting Miao, Cheng Group North Automatic Control Technology Institute Shanxi Taiyuan030006 China

ISBN: (纸本)9798350396157

This research presents a novel communication signal enhancement algorithm tailored for the low signal-to-noise ratio (SNR) scenarios in satellite communications. Departing from traditional linear processing, the algorithm exploits the bistable nature of stochastic resonant systems and exploits their nonlinear effects to enhance signals and suppress noise. Key optimizations include antenna system revisions, adjustments to improve signal coverage and strength, and strategic manipulation of electromagnetic wave emission positions. Collectively, these refinements address the challenges in mobile communication signals caused by multipath effects and transmission limitations, thereby advancing the development of wireless communication technology. The effectiveness of the proposed algorithm is demonstrated through a comprehensive review of recent advances in communication systems and systematic experiments that validate its performance in various scenarios. This innovative approach, encapsulated within a wireless communication system framework, promises to overcome SNR challenges in satellite communications, paving the way for improved signal quality in complex environments. © 2024 IEEE.

关键词： Signal to noise ratio

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Adaptive Learning-Based Path-Tracking control for Unknown Vehicle systems Under Performance Optimization

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-10页

作者： Xu, Yong Wan, Meng-Ying Wu, Zheng-Guang School of Automation Beijing Institute of Technology Beijing China Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

The state-of-the-art path-tracking control approaches for existing vehicle systems mostly rely on the accurate system dynamics and an initial stabilizing control policy assumption. To overcome those challenges, this paper presents an adaptive learning-based path-tracking control algorithm designed specifically for a completely unknown vehicle system without an initial stabilizing control strategy assumption. Firstly, a new variable is introduced to construct a new matrix thereby affording greater flexibility in selecting controller gains. Subsequently, leveraging this new matrix, a new policy iteration algorithm and an imitation-based policy iteration algorithm are concurrently proposed to achieve model-free learning path-tracking control in an optimal manner. In addition, an advanced data-driven switching policy iteration learning algorithm is developed to inherit the advantages of existing mainstream learning algorithms. When compared to several existing learning algorithms, the proposed algorithm not only eliminates the need for an initial stabilizing policy assumption but also exhibits faster convergence and reduced computational complexity. Finally, numerical simulations and comparisons are conducted to demonstrate the validity of the theoretical analysis. IEEE

关键词： Learning algorithms

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Coalition formation problem: a capability-centric analysis and general model

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Science China(Information Sciences) 2024年第11期67卷 180-193页

作者： Jie CHEN Miao GUO Bin XIN Qing WANG Shengyu LU Yipeng WANG Yulong DING School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering Tongji University

Coalition formation(CF) refers to reasonably organizing robots and/or humans to form coalitions that can satisfy mission requirements, attracting more and more attention in many fields such as multirobot collaboration and human-robot collaboration. However, the analysis on CF problems remains *** provide a valuable study reference for researchers interested in CF, this paper proposed a capabilitycentric analysis of the CF problem. The key problem elements of CF are firstly extracted by referencing the concepts of the 5W1H method. That is, objects(who) form coalitions(what) to accomplish missions(why) by aggregating capabilities(how) in a specific environment(where-when). Then, a multi-view analysis of these elements and their correlation in terms of capabilities is proposed through various logic diagrams, structure charts, etc. Finally, to facilitate a deeper understanding of capability-centric CF, a general mathematical model is constructed, demonstrating how the different concepts discussed in this analysis contribute to the overall model.

关键词： coalition formation capability aggregation capability metric mission requirement environmental effect

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An Improved De-noising Algorithm based on Empirical Mode Decomposition for Respiratory Sound Signals

An Improved De-noising Algorithm based on Empirical Mode Dec...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Niu, Jinglong Wang, Lin Shen, Shuai Chen, Zhishuai Pang, Jiwen Xue, Fan Yan North Automatic Control Technology Institute Taiyuan China

ISBN: (纸本)9798350337754

An enhanced noise-reduction algorithm utilizing empirical mode decomposition (EMD) has been introduced for the analysis of respiratory sound signals. As a method primarily driven by data, EMD offers significant capabilities in filtering out unwanted noise from signals. Combined with the wavelet thresholding principle and Hermite Interpolating Polynomial. In this study, we present a method that effectively distinguishes and separates the signal from the noise. Through the application of a defined threshold, we can acquire the modulus maxima for each intrinsic mode function (IMF) resulting from EMD decomposition. We employ the piecewise quintic Hermite Interpolating Polynomial to rebuild these IMFs. Upon successful reconstruction, the cleaned signal is derived by linearly superimposing the IMFs. Some experiments and simulation are carried out to confirm the efficiency of the improved de-noising algorithm. The results show that the result of classification is better using the improved EMD de-noising method than the result without using the de-noising method. © 2023 IEEE.

关键词： Empirical mode decomposition

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Comparison of Hierarchical MPC-Based Energy Management Strategies for Residential Microgrids

Comparison of Hierarchical MPC-Based Energy Management Strat...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Ye, Wenyan Chang, Hao-Hsuan Zhang, Ping Quakernack, Lars Kelker, Michael Haubrock, Jens Rptu Institute of Automatic Control Kaiserslautern Germany Hsbi Institute for Technical Energy Systems Bielefeld Germany

ISBN: (纸本)9789531842976

This paper compares three structures of model predictive control (MPC) approaches to address challenges in residential microgrids, mainly due to the incoincident time slot of available energy production and energy consumption. The control objective is to minimize the building energy consumption while fulfilling various constraints. The optimization problem takes into account the fluctuations in the energy demand. Through simulations, we evaluate the control performance under each approach, highlighting their trade-offs and suitability for different microgrid configurations. The simulation results offer valuable insights into the potential of MPC in optimizing residential energy management, guiding the selection of energy management system approaches that best align with specific operational goals. © 2024 IEEE.

关键词： Microgrids

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Dual Spatial-Temporal Feature Pyramid With Decoupled Temporal Mining for Video Semantic Segmentation

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Hong, Yuanduo Pan, Huihui Sun, Weichao Wang, Yulei Bian, Ning Gao, Huijun Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China Department of Control Science and Engineering Tongji University Shanghai China Dongfeng Motor Corporation Wuhan China

Semantic segmentation plays a pivotal role in environmental perception for autonomous driving. Video semantic segmentation (VSS) further takes temporal information into consideration for better scene parsing and temporal consistency. Previous research on VSS is mostly dedicated to developing new techniques (e.g. optical flows, attention) to better mine temporal information. In this work, we contribute from a different angle by efficiently incorporating multi-scale temporal information. The dual spatial-temporal feature pyramid is proposed to enable the direct enhancement of multi-scale features for target frames and unlash the design of temporal information mining modules. It contains a spatial feature pyramid from a target frame and a spatial-temporal feature pyramid from multiple reference frames. Building on the dual feature pyramid, we further propose to decouple motional contexts and static contexts to fully leverage temporal information. Specifically, multi-scale motional contexts are mined with the introduced dedicated module and static contexts are enhanced by making temporally fused category-level representations interact with the target frame feature. The final segmentation maps are obtained by regarding the enhanced category-level representations as powerful feature classifiers to classify the target frame feature of rich motional contexts. Experimental results on two popular VSS benchmarks demonstrate that the proposed method with decent parameter and inference efficiency clearly outperforms previous advanced methods. IEEE

关键词： Semantics

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