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Detection and classification of turn fault and high-resistance connection fault in inverter-fed permanent magnet machines based on high-frequency signals

Detection and classification of turn fault and high-resistan...

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作者： Hu, Rongguang Wang, Jiabin Mills, Andrew Chong, Ellis Sun, Zhigang Department of Electronics and Electrical Engineering University of Sheffield Sheffield United Kingdom Department of Automatic Control and System Engineering University of Sheffield Sheffield United Kingdom Electrical Capability Group Rolls-Royce plc Derby United Kingdom

Winding turn fault and high-resistance connection (HRC) fault will lead to different consequences and require different mitigation actions. In this study, the differentiating features between a turn fault and HRC fault are analysed and compared in a three-phase surface-mounted permanent magnet machine fed by the inverter with pulse-width-modulation voltages. The resultant high-frequency components in both voltages and currents are utilised for the fault detection and classification based on the high-frequency impedance and ripple current, without requiring modifications to the machine or interface design. Extensive simulations show that this method is capable of fault detection and classification in both transient and steady-state operations. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Permanent magnets

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Nash optimality based distributed model predictive control for vehicle platoon ⁎

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IFAC-PapersOnLine 2020年第2期53卷 6610-6615页

作者： Shuyou Yu Hao Chen Yangyang Feng Yajing Zhang Yongfu Li Christian Ebenbauer Hong Chen Department of Control Science and Engineering Jilin University Changchun 130012 P.R. China College of Automation Chongqing University of Posts and Telecommunications Chongqing 400065 P.R. China Institute for System Theory and Automatic Control University of Stuttgart Stuttgart 70550 Germany Clean Energy Automotive Engineering Tongji University Shanghai 201804 P. R. China

In this paper, a distributed model predictive control algorithm (DMPC) based on Nash optimality is proposed for automated vehicle platoon control. The optimization decision of vehicle platoon is decomposed into the decentralized optimization of single vehicles, in which the Nash optimality algorithm is adopted to solve the decentralized optimization problem. Thus, each vehicle can reach the local optimal target and the whole team can reach its Nash equilibrium. The methodology employs neighborhood information of the entire platoon through on-board sensors and V2V communication to achieve coordination of the entire platoon. The ability of the methods in terms of robustness to disturbances and cyber-physical interaction is demonstrated with simulation case studies.

关键词： Vehicle platoon Distributed control Model predictive control Nash optimality

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Hierarchical control with Guaranteed Fault Diagnosability

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IFAC-PapersOnLine 2018年第24期51卷 1105-1110页

作者： Stoican, Florin Petzke, Felix Prodan, Ionela Streif, Stefan University POLITEHNICA of Bucharest Automatic Control and Systems Engineering Department 313 Splaiul Independentei Bucharest Romania Technische Universität Chemnitz Automatic Control and System Dynamics Lab Chemnitz09107 Germany GrenobleINP France

A multiple time-scale hierarchical control approach with guarantees for active fault diagnosability (detection and isolation) is presented. Robust positive invariance notions are used to provide a set-membership test for FDI validation at the low level and sufficient constraints for guaranteeing FDI at the high level. Due to the computational burden of the involved bilinear optimization problem, the high-level reference governor operates at a slower sampling time than the controller of the low-level system. Therefore, corner cutting avoidance constraints are imposed such that the faster-sampled lower level is still guaranteed to function properly. A case study illustrates the presented theoretical notions. © 2018

关键词： Fault detection Edge detection Bilinear optimizations Computational burden Corner cutting Fault diagnosability Hierarchical control isolation Positive invariance Reference governors

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Distributed Nonconvex Optimization: Gradient-free Iterations and ϵ-Globally Optimal Solution

arXiv

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arXiv 2020年

作者： He, Zhiyu He, Jianping Chen, Cailian Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Automatic Control Laboratory ETH Zurich Zurich8092 Switzerland

Distributed optimization utilizes local computation and communication to realize a global aim of optimizing the sum of local objective functions. This article addresses a class of constrained distributed nonconvex optimization problems involving univariate objectives, aiming to achieve global optimization without requiring local evaluations of gradients at every iteration. We propose a novel algorithm named CPCA, exploiting the notion of combining Chebyshev polynomial approximation, average consensus, and polynomial optimization. The proposed algorithm is i) able to obtain ϵ-globally optimal solutions for any arbitrarily small given accuracy ϵ, ii) efficient in both zeroth-order queries (i.e., evaluations of function values) and inter-agent communication, and iii) distributed terminable when the specified precision requirement is met. The key insight is to use polynomial approximations to substitute for general local objectives, distribute these approximations via average consensus, and solve an easier approximate version of the original problem. Due to the nice analytic properties of polynomials, this approximation not only facilitates efficient global optimization, but also allows the design of gradient-free iterations to reduce cumulative costs of queries and achieve geometric convergence for solving nonconvex problems. We provide a comprehensive analysis of the accuracy and complexities of the proposed algorithm. © 2020, CC BY-NC-SA.

关键词： Polynomial approximation

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Optimization of Nostoc sp. biomass and protein composition in high-density cultivator based on DoE

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Algal Research 2025年 89卷

作者： Lucato, Veronica Ihadjadene, Yob Sut, Stefania Sforza, Eleonora Krujatz, Felix Department of Industrial Engineering DII University of Padova Via Marzolo 9 Padova 35131 Italy Institute of Natural Materials Technology Technische Universität Dresden Dresden 01069 Germany Chair of Automatic Control & System Dynamics Chemnitz University of Technology Chemnitz 09126 Germany Department of Pharmaceutical and Pharmacological Sciences University of Padova Via Marzolo 5 Padova 35131 Italy biotopa gGmbH – Center for Applied Aquaculture & Bioeconomy Radeberg 01454 Germany

High-density (HD) cultivation systems are a valuable alternative to improve the productivity of phototrophic microorganisms. They are designed to address the major challenges such as low cell densities, light attenuation, and inefficient gas exchange, offering innovative solutions. This work investigates the HD cultivation of the nitrogen-fixing cyanobacterium Nostoc sp. PCC 7120 under diazotrophic conditions, employing a hydrophobic membrane system for efficient CO₂ and N₂ transfer. A design of experiment (DoE) approach is applied to evaluate the influence of key operating variables, including light intensity, photoperiod, and phosphorus concentration, on biomass productivity (P_X) and nitrogen fixation (P_N). Mathematical models, describing the interactions between these process variables and growth responses are developed and validated, enabling the optimization of cultivation conditions to maximise productivity. Remarkable biomass productivity of 1.53 g_X L⁻¹ d⁻¹ was obtained in this system, under diazotrophic conditions. P_X was largely affected by light intensity, which should be supplied continuously, aligning with the ability of heterocystous species like Nostoc sp. of simultaneously perform photosynthesis and N-fixation. Additionally, phosphorus concentration was a critical parameter that must be precisely controlled to prevent substrate limitation or inhibition, with an optimal value of 34.1 mg_P L⁻¹. The produced biomass was further characterised with a focus on its nitrogen-rich molecules, particularly proteins, and nutritional value, assessed through essential amino acid content. The results showed that protein content was improved (53.4 %) at 280 μmol m⁻² s⁻¹, 25.5 mg_P L⁻¹_, and 18 h light period, with essential amino acid ranging between 11 % and 15 %. © 2025 The Authors

关键词： Amino acid profile Biomass productivity Nitrogen-fixing cyanobacteria Protein production Response surface methodology

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Constrained Extremum Seeking: a Modified-Barrier Function Approach ⁎

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IFAC-PapersOnLine 2019年第16期52卷 694-699页

作者： Christophe Labar Emanuele Garone Michel Kinnaert Christian Ebenbauer Department of Control Engineering and System Analysis Université libre de Bruxelles 1050 Brussels Belgium Institute for Systems Theory and Automatic Control University of Stuttgart 70569 Stuttgart Germany

In this paper, we address the problem of steering the input of a convex function to a value that minimizes the function under a convex constraint. We consider the case where the constraint cannot be violated of more than a user-defined value during the whole transient phase. The mathematical expression of both the cost function and the constraint are assumed to be unknown. The only information available are the on-line values of the cost and the constraint. To tackle this problem, an optimization law, based on a modified-barrier function, and involving the gradient of both the cost function and the constraint, is firstly designed. The Lie bracket formalism is then exploited to approximate this law, by combining time-periodic signals with the on-line measurements of both the cost and the constraint. The stability property of the resulting constrained extremum seeking system is proved, and its effectiveness is shown in simulation.

关键词： Constrained Optimization Extremum Seeking Singular Perturbations Data-based control Modified Barrier-Function

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A Hierarchical Architecture for the Coordination of an Ensemble of Steam Generators

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IFAC-PapersOnLine 2020年第2期53卷 11557-11562页

作者： Stefano Spinelli Elia Longoni Marcello Farina Felix Petzke Stefan Streif Andrea Ballarino Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Italy Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato Consiglio Nazionale delle Ricerche Department of Electrical Engineering and Information Technology Technische Universität Chemnitz Automatic Control and System Dynamics Lab

This work presents a hierarchical architecture for the optimal management of an ensemble of steam generators, which needs to jointly sustain a common load. The coordination of independent subsystems is provided by a multi-layer control scheme. A high-level optimizer computes the optimal shares of production to be allocated to single generators. At medium level, a robust tube-based model predictive control (MPC) is proposed to track the time-varying demand of the ensemble using a centralized, but aggregated model, whose order does not scale with the number of subsystems. At low level, decentralized controllers are in place to stabilize the internal boiler pressure. The control architecture enables the dynamic modification of the ensemble configuration and plug and play operations. Simulation results are reported to demonstrate the potentialities of the proposed approach.

关键词： Model predictive optimization-based control Optimization control of large-scale network systems Hierarchical multilevel multi-layer control Steam generator Energy systems

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Extremum seeking algorithms based on non-commutative maps 11

Extremum seeking algorithms based on non-commutative maps

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11th IFAC Symposium on Nonlinear control systems, NOLCOS 2019

作者： Feiling, Jan Labar, Christophe Grushkovskaya, Victoria Garone, Emanuele Kinnaert, Michel Ebenbauer, Christian Institute for Systems Theory and Automatic Control University of Stuttgart Germany Dr. Ing. h.c. F. Porsche AG Stuttgart Germany Department of Control Engineering and System Analysis Université libre de Bruxelles Belgium Institute for Mathematics Julius-Maximilians-University Würzburg Germany

In this work, discrete-time extremum seeking algorithms for unconstrained optimization problems are developed. A general class of non-commutative maps and one- and two point function evaluation polices are presented to approximate a gradient-descent algorithm, suitable for extremum seeking problems. Moreover, adaptive step size rules are discussed to achieve faster convergence and vanishing steady state oscillations. © 2019, IFAC (International Federation of automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Optimization

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Attitude control of hypersonic vehicle based on optimized ADRC 8

Attitude control of hypersonic vehicle based on optimized AD...

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8th IEEE Data Driven control and Learning systems Conference, DDCLS 2019

作者： Piao, Minnan Sun, Mingwei Huang, Jian Wang, Zenghui Chen, Zengqiang Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China College of Artificial Intelligence Nankai University Tianjin300350 China Beijing Automatic Control and Equipment Institute Beijing100074 China University of South Africa Department of Electrical and Mining Engineering Florida1710 South Africa

ISBN: (纸本)9781728114545

In this paper, two types of practical angle of attack control schemes are proposed for hypersonic vehicle which is subject to large unmodeled, parametric uncertainties and external disturbances. In the first scheme, the pitch angle control method based on the second-order linear active disturbance rejection control is directly applied to the angle of attack control through simple command transformation. Inner-loop pitch angular rate feedback is performed first to enhance the damping in the second scheme, and then first-order linear active disturbance rejection control is designed for the overdamped plant. Both schemes provide simple and robust solutions to the angle of attack control. To achieve desired stability and performance robustness, non-smooth $H-{\infty}$ synthesis technique is utilized to optimize the controller within the designed flight envelope. Nonlinear simulations are performed to validate the advantages of the proposed methods. © 2019 IEEE.

关键词： Hypersonic vehicles

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LDGCN: An Edge-End Lightweight Dual GCN Based on Single-Channel EEG for Driver Drowsiness Monitoring

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IEEE Transactions on Consumer Electronics 2025年

作者： Huang, Jingwei Wang, Chuansheng Huang, Jiayan Fan, Haoyi Xue, Xingsi Zhang, Fuquan Fuzhou University College of Computer and Big Data Fuzhou China Polytechnic University of Catalonia Department of Automatic Control Barcelona Spain Putian University New Engineering Industry College Putian China Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian Fuzhou350118 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China Minjiang University College of Computer and Control Engineering Fuzhou China Sichuan Conservatory of Music Digital Media Art Key Laboratory of Sichuan Province Chengdu China Minjiang University Fuzhou Technology Innovation Center of Intelligent Manufacturing information System Fuzhou China Fuzhou China

Driver drowsiness electroencephalogram (EEG) signal monitoring can promptly alert drivers of their drowsiness in edge-end Consumer Electronics (CE), thereby reducing the probability of traffic accidents. Graph convolutional networks (GCNs) have shown significant advancements in processing the non-stationary, time-varying, and non-Euclidean nature of EEG signals. However, the existing single-channel EEG adjacency graph construction process lacks interpretability, which hinders the ability of GCNs to effectively extract adjacency graph features, thus affecting the performance of drowsiness monitoring. To address this issue, we propose an edge-end Lightweight Dual Graph Convolutional Network (LDGCN). Specifically, we are the first to incorporate neurophysiological knowledge to design a Baseline Drowsiness Status Adjacency Graph (BDSAG), which characterizes driver drowsiness status. Additionally, to express more features within limited EEG data, we introduce the Augmented Graph-level Module (AGM). This module captures global and local information at the graph level, ensuring that BDSAG features remain intact while enhancing effective feature expression capability. To further enhance the application of CE, we apply Adaptive Pruning Optimization (APO) to the channels and neurons of LDGCN, which nearly halves the inference latency. Experiments on benchmark datasets demonstrate that LDGCN offers the best trade-off between monitoring performance and hardware resource utilization, outperforming existing state-of-the-art algorithms. © 1975-2011 IEEE.

关键词： Neurons

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