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Disturbance Observer-based Pointing control of Leighton Chajnantor Telescope

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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Continuous Non-Singular Terminal Sliding Mode control for High Pressure Common Rail systems Using a FTDO 41

Continuous Non-Singular Terminal Sliding Mode Control for Hi...

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第41届中国控制会议

作者： Zheng Yuan Chen Dai Hao Sun Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

High pressure common rail(HPCR) technology has been widely applied in diesel *** tracking speed and the steady-state fluctuations of the rail pressure determine the performance of the HPCR *** this paper,the fuel injection disturbance which has a main impact on rail pressure fluctuations is fully *** on fluid dynamics and Newtonian mechanics,a nonlinear model of the HPCR system is *** order to suppress the fuel injection disturbance,a finitetime disturbance observer(FTDO) based continuous non-singular terminal sliding mode controller(CNTSMC+FTDO) is designed based on the three-step analysis *** is proved that the system tracking error can converge to the equilibrium point in a finite ***,a group of simulations and experiments are conducted in Simulink and the more realistic AMESim environment respectively and the results verify the effectiveness and feasibility of the proposed algorithm.

关键词： High pressure common rail Non-singular terminal sliding mode FTDO Rail pressure control AMESim

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Robotic Etiquette:Socially Acceptable Navigation of Service Robots with Human Motion Pattern Learning and Prediction

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Journal of Bionic engineering 2010年第2期7卷 150-160页

作者： Kun Qian,Xudong Ma,Xianzhong Dai,Fang Fang key Lab of measurement and control of complex systems of engineering (Ministry of Education,China), Southeast University,Nanjing 210096,P.R.China [a] Key Lab of Measurement Control of Complex Systems of Engineering (Ministry of Education China) Southeast University Nanjing 210096 P. R. China

Nonverbal and noncontact behaviors play a significant role in allowing service robots to structure their interactions *** this paper, a novel human-mimic mechanism of robot’s navigational skills was proposed for developing sociallyacceptable robotic *** on the sociological and physiological concerns of interpersonal interactions in movement,several criteria in navigation were represented by constraints and incorporated into a unified probabilistic cost grid for safemotion planning and control, followed by an emphasis on the prediction of the human’s movement for adjusting the robot’spre-collision navigational *** human motion prediction utilizes a clustering-based algorithm for modeling humans’indoor motion patterns as well as the combination of the long-term and short-term tendency prediction that takes into accountthe uncertainties of both velocity and heading *** simulation and real-world experiments verified the effectivenessand reliability of the method to ensure human’s safety and comfort in navigation.A statistical user trials study was also given tovalidate the users’favorable views of the human-friendly navigational behavior.

关键词： robotic etiquette navigation human motion prediction human-robot interaction service robot

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Extended State Observer Based Adaptive control Scheme for PMSM System 33

Extended State Observer Based Adaptive Control Scheme for PM...

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第三十三届中国控制会议

作者： Li Xiaodi Li Shihua School of Automation Southeast University Key laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (纸本)9781479947249

In this paper, the speed regulation problem for permanent magnet synchronous motor(PMSM) systems under vector control framework is studied. A modified composite control strategy combining model reference adaptive control(MRAC)method and extended state observer(ESO) technology, called MRAC+ESO method, is proposed. controller is designed for the speed loop of the permanent magnet synchronous motor(PMSM) to improve the performance of the system. The stability analysis, simulation and experimental results are presented to show the effectiveness of the proposed control method.

关键词： Model reference adaptive control(MRAC),Permanent magnet synchronous motor(PMSM),Speed regulation system,Extended state observer(ESO),Composite controller

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A Hybrid Data-Driven Granular Model for Battery Remaining Useful Life Prediction

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IEEE Transactions on Instrumentation and measurement 2025年 74卷

作者： Jing, TaiLong Du, Sheng Wang, Cong Wu, Chao Pedrycz, Witold Sharaf, Mohamed Li, ZhiWu Luoyang Institute of Science and Technology School of Electrical Engineering and Automation Luoyang471023 China 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 Xi’an710072 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland King Saud University College of Engineering Department of Industrial Engineering Riyadh11421 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology Macau China

Accurate and meaningful prediction of the remaining useful life (RUL) of lithium-ion batteries (LIBs) provides a significant guide for the maintenance and management of these LIBs. A singular numerical predictive result by numerous conventional models is insufficient to furnish decision-makers with comprehensive or nuanced insights. To address this issue, predictive RUL results in the form of information granules are essential. In this study, a hybrid data-driven granular model is established for battery RUL prediction with granular (interval-based) quantification for LIBs. This granular model is designed and formulated in a way that it produces comprehensive prediction outcomes realized as information granules, which are expressed in a more descriptive and comprehensive manner. Thus, the resulting information granules can effectively reflect and communicate the confidence associated with the predictions. The granular model is realized in two steps: 1) probabilistic prediction results are produced by a hybrid numeric predictive model and 2) a comprehensive granulation of the probabilistic results is achieved under the principle of information granularity. The granular predictive results are holistically evaluated and optimized by the two associated criteria of granularity (coverage and specificity). This transformation of information granules provides an intuitive and interpretable display for battery maintenance and safe work. The proposed granular model is verified by using an open-access LIBs dataset, and the experimental results demonstrate that the proposed granular model outperforms other comparative methods. © 2025 IEEE. All rights reserved.

关键词： Prediction models

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Cooperative Hierarchical Coverage control of Multi-Agent systems with Non-holonomic Constraints in Poriferous Environments

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IEEE Transactions on control of Network systems 2025年

作者： Zou, Jiayu Zhang, Hai-Tao Zhai, Chao Xing, Ning Ma, Yong Liu, Xingjian Huazhong University of Science and Technology School of Artificial Intelligence and Automation The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China China University of Geosciences School of Automation China The MOE Engineering Research Center of Intelligent Technology for Geo-Exploration Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Academician Workstation of China COSCO Shipping Corporation Ltd. Shanghai200120 China Wuhan University of Technology Sanya Science and Education Innovation Park Sanya572000 China Wuhan University of Technology Chongqing Research Institute Chongqing401120 China

It has long posed a challenging task to optimally deploy multi-agent systems (MASs) to cooperatively coverage poriferous environments in real cooperative detection applications. In response to this challenge, this paper proposes a hierarchical coverage control (HCC) protocol for MASs to perform sector-based coverage operations. First, a distributed Voronoi partition-based sweep-and-assign protocol, combined with a sectorial partition method, is developed, enabling the segmentation of a whole poriferous region into multiple sectorial sub-subregions. Following this procedure, an extreme search scheme is developed to determine the optimal amount of agents for each subregion. After this allocation, a distributed controller is proposed to deploy the agents, considering non-holonomic constraints, into designated niche positions. Additionally, sufficient conditions are derived to guarantee the asymptotical stability of the present HCC. The analytical challenge of the present study stems from the non-convex characteristics inherent in the loss function induced by porous environments. This non-convexity renders the task of globally optimizing the assignment of MASs intractable. Finally, numerical simulations are conducted to validate the effectiveness of the present coverage control approach. © 2014 IEEE.

关键词： Nonlinear control systems

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Effect of New Dual-Credit Policy on Electric Vehicle Diffusion in China

SSRN

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SSRN 2025年

作者： Zhao, Dan Wang, Jian Li, Wen-Wu Huang, Shuai Tang, Jin-Huan School of Management Science and Engineering Anhui University of Technology Ma'anshan243032 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Ma'anshan243002 China School of Economics and Management Shenyang Aerospace University Shenyang110136 China School of Business Qingdao University Qingdao266071 China

The impact of new dual-credit policy on electric vehicle (EV) diffusion is examined through complex network evolutionary game theory, we find that merely tightening new energy vehicle (NEV) credit rule and corporate average fuel consumption (CAFC) credit rule may not necessarily benefit the growth of auto industry. This paper further discusses the influence of different update strategies on EV diffusion. The results indicate that with the increase of NEV credit accounting coefficient, the upper limit of threshold interval of NEV credit trading price remains unchanged, while lower limit decreases. With the decrease of ratio of standard CAFC to target CAFC or the increase of requirement of NEV credits for fuel vehicle manufacturer, the upper and lower limits of threshold interval of NEV credit price are reduced. With the increasing network scale, the driving effect of Fermi function is gradually superior to EWA algorithm. © 2025, The Authors. All rights reserved.

关键词： Automotive industry

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Global State control for a Class of Inherently Higher-order Parameterized Nonlinear Time-delay systems Based on Homogeneous Domination Approach

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IFAC-PapersOnLine 2015年第12期48卷 191-196页

作者： Chai, Lin Wang, Pan Fei, Shumin Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Ministry of Education School of Automation Nanjing 210096 China

This paper addresses the problem of global state feedback stabilization for a class of inherently higher-order parameterized nonlinear systems subject to time-delay. By using the homogeneous domination approach, we construct a homogeneous state feedback controller with an adaptive strategy. A constructive design method is developed based an effective coupling of the inductive method and a sign function, leading to adaptive regulators with minimal parameterization. With the aid of a homogeneous Lyapunov-Krasovskii functional, the closedloop systems can be asymptotically stabilized globally. © 2015, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Parameterization

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SmokeAgent: Multimodal agent for fine-grained smoke event analysis in large-scale wild environments

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Pattern Recognition 2025年 167卷

作者： Cao, Yichao Yang, Feng Li, Xuanpeng Lu, Xiaobo School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China School of Instrument Science and Engineering Southeast University Nanjing210096 China

In recent years, numerous outstanding works have emerged in the field of smoke recognition;however, challenges related to fine-grained analysis and intelligence persist in wild application scenarios. This paper approaches the problem from a new perspective, designing the first interactive Fine-Grained Smoke Analysis Agent (dubbed as SmokeAgent). Unlike traditional smoke detectors, SmokeAgent ingeniously integrates a Multi-modal Foundation Model (MFM) to detect non-rigid, semi-transparent smoke objects. It not only provides accurate fine-grained smoke category predictions but also achieves interactive close-up observations through camera manipulation. Specifically, leveraging the existing feature learning capacity of the MFM, we first design a general smoke recognition module, followed by a spatial prompt-based feature mining method to enhance the MFM's ability to analyze local smoke targets. We also design an action space for camera manipulation, allowing the agent to dynamically retrieve information and refine its fine-grained cognition in wild scenarios. Additionally, we collected the first dataset that includes both wide shot and close-up images, covering fine-grained categories such as agricultural smoke, forest fire smoke, industrial emissions, residential smoke, and fog. Extensive experiments demonstrate that the proposed SmokeAgent model offers more fine-grained and intelligent detection capabilities in wild scenarios compared to traditional smoke detectors. © 2025

关键词： Smoke detectors

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Balanced prioritized experience replay in off-policy reinforcement learning

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Neural Computing and Applications 2024年第25期36卷 15721-15737页

作者： Lou, Zhouwei Wang, Yiye Shan, Shuo Zhang, Kanjian Wei, Haikun Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China School of Automation Southeast University Nanjing210096 China

In Off-Policy reinforcement learning (RL), the experience imbalance problem can affect learning performance. The experience imbalance problem refers to the phenomenon that the experiences obtained by the agent during the learning process are unevenly distributed in the state space, resulting in the agent’s inability to accurately estimate the value of each potential state. This problem is typically caused by environments with high-dimensional state and action spaces, as well as the exploration–exploitation mechanism inherent in RL. This article proposes a balanced prioritized experience replay (BPER) algorithm based on experience rarity. First, an evaluation metric to quantify experience rarity is defined. Then, the sampling priority of each experience is calculated according to this metric. Finally, prioritized experience replay is performed according to the sampling priority. BPER increases the sampling frequency of high-rarity experiences and decreases the sampling frequency of low-rarity experiences, enabling the agent to learn more comprehensive knowledge. We evaluate BPER on a series of MuJoCo continuous control tasks. Experimental results show that BPER can effectively improve the learning performance while mitigating the impact of the experience imbalance problem. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Reinforcement learning

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