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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Ozgen, Zeynep Soyyigit Yildiran, Ugur Yildiz Technical University Control and Automation Engineering Davutpasa Campus Istanbul Turkey

ISBN: (纸本)9798350360165

In this study, ANN (Artificial Neural Network) and ARX (Auto Regressive eXogenous) prediction structures were compared, and tested on a heating system. Different ANN structures were also compared within the study, and the network RMSE (Root Mean Square Error) and ME (Mean Error) values were highlighted. The used ANN structures vary in a single hidden layer with node counts of 5,7,9, and 11, while the input values are examined in two groups as two-step back (second order) or one step back (first order), and the training and test results of these structures are investigated. © 2024 IEEE.

关键词： Heating equipment

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Model-Based Online Adaptive Inverse Noncooperative Linear-Quadratic Differential Games via Finite-Time Concurrent Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4247-4257页

作者： Lin, Jie Wu, Huai-Ning Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beijing100191 China Peng Cheng Laboratory Shenzhen518066 China

Noncooperative differential games provide a basis for the study of coordination, conflict, and control for a single dynamical system with multiple players. Within the linear-quadratic differential games (LQDGs), the optimal feedback gain matrix and the weighting matrices of individual cost function depict each player's control policy and the tradeoff of various objectives, respectively. In this article, we investigate the inverse problem of LQDG with partial state observation via a model-based online method, i.e., recover the cost function of each player. First, a state observer is used to estimate the system state. Then, the feedback gain matrices of players are learned using a finite-time concurrent learning (FTCL)-based adaptive law relaxing the persistent excitation (PE) condition which is required in traditional adaptive estimation methods. With the learned feedback gain matrices, a semidefinite programming (SDP) problem with the quadratic objective function can be set up for determining the weighting matrices of the cost function. The applicability and effectiveness of the proposed method are demonstrated with a numerical example and a shared steering control simulation. © 2020 IEEE.

关键词： Cost functions

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Attitude control of flexible satellite via three-dimensional magnetically suspended wheel

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Applied Mathematics and Mechanics(English Edition) 2025年第3期46卷 555-572页

作者： J.TAYEBI Yingjie CHEN Ti CHEN Shiyuan JIA State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China School of Intelligent Engineering and Automation Beijing University of Posts and TelecommunicationsBeijing 100876China

This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorporating flexible appendages and an orthogonal cluster of magnetically suspended reaction wheel actuators is initially *** that,an adaptive attitude controller is designed with a switching surface of variable structure,an adaptive law for estimating inertia matrix uncertainty,and a fuzzy disturbance observer for estimating disturbance ***,a Moore-Penrose-based steering law is proposed to derive the tilt angle commands of the orthogonal configuration of the 3D MSW to follow the designed control ***,numerical simulations are presented to validate the effectiveness of the proposed control strategy.

关键词： flexible satellite three-dimensional(3D)magnetically suspended wheel(MSW) attitude control adaptive control disturbance observer

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Fast Distance Protection Scheme for Wind Farm Transmission Lines Considering R-L and Bergeron Models

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 840-852页

作者： Zepeng Hu Bin Li Yuping Zheng Tonghua Wu Jiawei He Bin Yao Yaru Sheng Wei Dai Xindong Li Electrical Engineering and Automation Tianjin UniversityTianjinChina State Key Laboratory of Smart Grid Protection and Control NARI Group CorporationNanjingChina

The distributed capacitance of the line becomes larger as the scale of wind farms,the transmission voltage level,and the transmission distance ***,the error of the traditional time-domain distance protection scheme based on the R-L model,which ignores the distributed capacitance of the line,becomes ***,the error of the time-domain fault location method based on the R-L model,especially the maximum error range,is theoretically analyzed in this *** this basis,a novel fault location method based on the RL and Bergeron models is ***,a fast time-domain distance protection scheme is *** the proposed scheme,the error in the fitting calculation is used to construct a weight matrix,and an algorithm for solving the time-domain differential equations is designed to improve the calculation speed and *** with the traditional frequency-domain distance protection scheme,the proposed scheme is independent of the power supply characteristics;thus,it is suitable for wind farm transmission *** addition,compared with the traditional method based on the R-L model,the proposed scheme effectively avoids the negative influence of the distributed capacitance of the line,which significantly improves the operating *** types of faults are simulated by PSCAD/EMTDC to verify the effectiveness and superiority of the proposed scheme.

关键词： Transmission line R-L model time-domain distance protection wind farm

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Proton Exchange Membrane Fuel Cell Thermal System Modeling and control 10

Proton Exchange Membrane Fuel Cell Thermal System Modeling a...

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10th International Conference on Electrical and Electronics engineering, ICEEE 2023

作者： Özdemir, Tuna Han Yasar, Claudia Fernanda Yildiz Technical University Avl Research and Engineering Department of Control and Automation Engineering Istanbul Turkey Yildiz Technical University Department of Control and Automation Engineering Istanbul Turkey

ISBN: (纸本)9798350304299

The urgent issue of global warming and its adverse effects, including wildfires, water scarcity, and the spread of diseases, calls for concerted efforts to mitigate emissions and curb climate change. Among the effective strategies is the reduction of carbon emissions, for which hydrogen-powered proton exchange membrane fuel cell systems are vital. These systems generate electricity through chemical reactions involving hydrogen, with only water and heat as byproducts, hence their environmentally friendly nature. Fuel cell efficiency is higher than conventional systems depending on the type and the operating temperature. Proper thermal control is essential for maintaining high efficiency. This research paper aims to examine standard models of proton exchange membrane fuel cell thermal systems and suggest an efficient control approach. The system dynamics are derived from fundamental models, and an adaptive PID controller is simulated with MATLAB/Simulink. The paper also presents a comparative analysis between traditional PID control and adaptive PID, an advanced control technique. © 2023 IEEE.

关键词： Three term control systems

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Attention-Modulated Feature Fusion Neural Network for Inverse Modeling of Microwave Filters

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 376-379页

作者： Guo, Linwei Cao, Weihua Hu, Wenkai Lu, Zhengyang Wu, Min China University of Geosciences School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make full use of features from multiple perspective is a critical issue for improving model accuracy. To solve it, this letter proposes an attention-modulated feature fusion neural network (AMFFNN). AMFFNN achieves multiperspective feature fusion (MPFF) at the input side and independent feature fusion (IFF) at the output side. In addition, feature fusion in AMFFNN is enhanced by attention modules to dynamically identify the importance of each feature. Statistical and comparative results of simulations demonstrate that AMFFNN outperforms existing methods in terms of accuracy, stability, and generalization. © 2023 IEEE.

关键词： Inverse problems

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An enhanced stochastic error modeling using multi-Gauss–Markov processes for GNSS/INS integration system

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Journal of engineering and Applied Science 2024年第1期71卷 186页

作者： Wu, Youlong Chen, Shuai School of Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing China School of Automation Nanjing University of Science and Technology Nanjing China

Angular random walk (ARW), rate random walk (RRW), and bias instability (BI) are the main noise types in inertial measurement units (IMUs) and thus determine the navigation performance of IMUs. BI is the flicker noise, which determines the noise level of an inertial sensor. The traditional error modeling approach involves modeling the ARW and BI processes as RRW or Gauss–Markov (GM) processes, and this approach is applied as a suboptimal filter in the global navigation satellite system (GNSS)/inertial navigation system (INS) extended Kalman filter (EKF). In this paper, the random error identification processes for white noise and colored noise for inertial sensors are separated using the Allan variance and power spectral density methods and the equivalence of the stochastic process differential equations of bias instability and a combination of multiple first-order GM processes are derived. A colored noise compensation method is proposed based on the enhanced EKF model. Experimental results demonstrate that, compared to traditional error models, our proposed model reduces positional drift error in dynamic testing from 195 to 49 m, enhancing positional accuracy by 40.2%. These findings confirm the potential and superiority of our method in complex navigation environments. © The Author(s) 2024.

关键词： Markov processes

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Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 595-607页

作者： Jianguo Zhao Chunyu Yang Weinan Gao Linna Zhou Xiaomin Liu the Engineering Research Center of Intelligent Control for Underground Space Ministry of EducationChina University of Mining and TechnologyXuzhou 221116 the School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116 IEEE the State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation *** the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost *** the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement *** combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop *** proposed decomposition design not only bypasses the numerical stiffness but also alleviates the *** efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.

关键词： Adaptive optimal control decentralized control output regulation reinforcement learning(RL) singularly perturbed systems(SPSs)

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Predictor and ESO-based adaptive tracking control of heterogeneous vehicle platoon

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Science China(Technological Sciences) 2024年第9期67卷 2842-2852页

作者： SUN ZhiZe LIU Yang ZHANG LinChuang College of Control Science and Engineering Bohai UniversityJinzhou 121013China College of Automation and Electronic Engineering Qingdao University of Science and TechnologyQingdao 266061China College of Information Science and Technology Bohai UniversityJinzhou 121013China

This paper investigates the distributed adaptive platoon tracking problem of third-order heterogeneous vehicles subject to model uncertainties. The design process is divided into two steps. Firstly, an adaptive tracking controller is designed for the dynamic leading vehicle. And then, the distributed adaptive controllers are established for followers. Moreover, the predictor technique is used to improve the estimate performance of the adaptive law, and the total disturbance is approximated and compensated by the variable gain nonlinear extended state observers(NESOs) driven by the estimation error. By introducing the variable gain hyperbolic tangent tracking differentiator(HTTD), the “complexity explosion” problem is avoided. The feasibility and effectiveness of the proposed protocol are verified by simulation tests.

关键词： variable gain NESOs heterogeneous vehicles platoon tracking predictor

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Disturbance Observer-based Pointing control of Leighton Chajnantor Telescope

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Research in Astronomy and Astrophysics 2024年第1期24卷 135-150页

作者： Weirui Chen Zheng Wang School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China

Leighton Chajnantor Telescope(LCT), i.e., the former Caltech Submillimeter Observatory telescope, will be refurbished at the new site in Chajnantor Plateau, Chile in 2023. The environment of LCT will change significantly after its relocation, and the telescope will be exposed to large wind disturbances directly because its enclosure will be completely open during observation. The wind disturbance is expected to be a challenge for LCT's pointing control since the existing control method cannot reject this disturbance very well. Therefore, it is very necessary to develop a new pointing control method with good capability of disturbance rejection. In this research, a disturbance observer—based composite position controller(DOB-CPC) is designed, in which an H∞feedback controller is employed to compress the disturbance, and a feedforward linear quadratic regulator is employed to compensate the disturbance precisely based on the estimated disturbance signal. Moreover, a controller switching policy is adopted, which applies the proportional controller to the transient process to achieve a quick response and applies the DOB-CPC to the steady state to achieve a small position error. Numerical experiments are conducted to verify the good performance of the proposed pointing controller(i.e., DOB-CPC) for rejecting the disturbance acting on LCT.

关键词： instrumentation:miscellaneous methods:analytical methods:numerical telescopes

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