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A Recursive System Identification With Non-Uniform Temporal Feedback Under Coprime Collaborative Sensing

ASME Letters in Dynamic systems and Control 2023年第2期3卷 021010页

作者： Ouyang, Jinhua Chen, Xu Mechatronics Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States Mechatronics Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States

We present a system identification method based on recursive least-squares (RLS) and coprime collaborative sensing, which can recover system dynamics from non-uniform temporal data. Focusing on systems with fast input sampling and slow output sampling, we use a polynomial transformation to reparameterize the system model and create an auxiliary model that can be identified from the non-uniform data. We show the identifiability of the auxiliary model using a Diophantine equation approach. Numerical examples demonstrate successful system reconstruction and the ability to capture fast system response with limited temporal feedback. Copyright © 2023 by ASME.

关键词： Feedback

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Real-Time Implementation of MEKF using VDPL Localization Algorithm by Utilizing MATLAB & ROS Communication

Real-Time Implementation of MEKF using VDPL Localization Alg...

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2024 Innovations in Intelligent systems and Applications Conference, ASYU 2024

作者： Altınpınar, Ozan Vahit Contarlı, Emre Can Sezer, Volkan Department of Mechatronics Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul Turkey Department of Control and Automation Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9798350379433

Mobile robots, which are produced to fulfill certain tasks to make our lives easier, are becoming more and more common in our environment day by day. In the long run, these robots can be more cost-effective, faster, and more efficient than humans in accomplishing tasks. In order for mobile robots to fulfill the tasks, they need to be able to safely navigate to specific destinations without hitting obstacles. Safely reaching a given goal most accurately and shortly is the problem of autonomy. This autonomy problem is divided into sub-problems and algorithms are needed to solve each sub-problem. The main sub-problems in the field of autonomy are localization, mapping, local planning, and global planning. The main purpose of this paper is to describe how the position information computed by a MEKF (Modified Extended Kalman Filter) localization algorithm using the VDPL (Virtual Dynamic Point Landmark) algorithm, which was previously designed in MATLAB, is published to the ROS environment via a topic. This position information can be used together with the local and global planning algorithms in the navigation stack to realize fully autonomous driving capability in a real-time environment. Using these algorithms, full-autonomous driving tests were conducted on the Turtlebot3 mobile robot in a real-time environment according to a predefined scenario. The performance results of both simulation and real-world tests show that the MEKF using the VDPL algorithm outperforms the AMCL algorithm in the navigation stack in both cases. © 2024 IEEE.

关键词： Extended Kalman filters

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Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

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Decentralized Model-Free Prescribed Performance Control for Interconnected systems

Decentralized Model-Free Prescribed Performance Control for ...

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第35届中国控制与决策会议

作者： Jinxi Zhang Tianyou Chai Yangquan Chen State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Mechatronics Embedded Systems and Automation Lab University of CaliforniaMerced

This paper is dealt with the problem of decentralized prescribed performance control(PPC) for the interconnected systems composed of feedback linearizable *** the restrictive conditions in the related studies,the interconnections need merely to be continuous in this ***,this study is focused on the model-free control design,i.e.,no prior knowledge of the system model is used for the controller,except for the most fundamentally structural *** solve the problem,a novel decentralized model-free PPC approach is *** skilful combination of the orientation function and the barrier function yields a model-free PPC,without approximation,identification,adaptation,*** adopting the dialectic by contradiction to establish the control performance,instead of the Lyapunov stability theory,it is revealed that the proposed control is inherently robust against the *** simulation results on the inverted double pendulums demonstrate the effectiveness of our approach.

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Real-Time Implementation of MEKF using VDPL Localization Algorithm by Utilizing MATLAB & ROS Communication

Real-Time Implementation of MEKF using VDPL Localization Alg...

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Innovations in Intelligent systems and Applications Conference

作者： Ozan Vahit Altinpinar Emre Can Contarlı Volkan Sezer Department of Mechatronics Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul TURKEY Department of Control and Automation Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul TURKEY

ISBN: (数字)9798350379433

ISBN: (纸本)9798350379440

关键词： Location awareness Technological innovation Navigation Heuristic algorithms Real-time systems Planning Mobile robots Kalman filters MATLAB Intelligent systems

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Predictive Battery Cooling in Heavy-Duty Fuel Cell Electric Vehicles 10th

Predictive Battery Cooling in Heavy-Duty Fuel Cell Electric ...

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10th IFAC Symposium on Advances in Automotive Control, AAC 2022

作者： Büyüker, Banu Ç. Ferrara, Alessandro Hametner, Christoph Institute of Mechanics and Mechatronics Division of Process Control and Automation TU Wien Vienna Austria Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria

In electric vehicles, it is essential to prevent battery overheating due to excessive ohmic losses or inadequate cooling. Indeed, the temperature of battery systems significantly impacts their performance, lifetime, and safety. This paper proposes a predictive cooling optimization method for the battery thermal management system of heavy-duty fuel cell electric vehicles. The predictive cooling strategy is based on a model predictive control (MPC) formulation to maintain the battery temperature in its optimal range (to increase efficiency) and avoid high-temperature peaks (to increase lifetime and safety). The predictive thermal management relies on the ohmic losses forecast provided by a predictive energy management system. Simulations of a real-world driving cycle validate the proposed MPC and assess the impact of the predictive horizon length, which is critical for thermal management performance. The comparison against a simple hysteresis control strategy highlights the significant benefits of the proposed MPC for higher battery efficiency and lifetime. Copyright © 2022 The Authors.

关键词： Model predictive control

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Decentralized Model-Free Prescribed Performance Control for Interconnected systems

Decentralized Model-Free Prescribed Performance Control for ...

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Chinese Control and Decision Conference, CCDC

作者： Jinxi Zhang Tianyou Chai Yangquan Chen State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Mechatronics Embedded Systems and Automation Lab University of California Merced Merced USA

This paper is dealt with the problem of decentralized prescribed performance control (PPC) for the interconnected systems composed of feedback linearizable systems. Without the restrictive conditions in the related studies, the interconnections need merely to be continuous in this paper. Moreover, this study is focused on the model-free control design, i.e., no prior knowledge of the system model is used for the controller, except for the most fundamentally structural information. To solve the problem, a novel decentralized model-free PPC approach is developed. The skilful combination of the orientation function and the barrier function yields a model-free PPC, without approximation, identification, adaptation, etc. By adopting the dialectic by contradiction to establish the control performance, instead of the Lyapunov stability theory, it is revealed that the proposed control is inherently robust against the interconnections. The simulation results on the inverted double pendulums demonstrate the effectiveness of our approach.

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Investigating the dynamic memory effect of human drivers via ON-LSTM

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Science China(Information Sciences) 2020年第9期63卷 83-93页

作者： Shengzhe DAI Zhiheng LI Li LI Dongpu CAO Xingyuan DAI Yilun LIN Department of Automation Tsinghua University Shenzhen International Graduate School Tsinghua University Department of Mechanical and Mechatronics Engineering University of Waterloo State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

It is a widely accepted view that considering the memory effects of historical information(driving operations) is beneficial for vehicle trajectory prediction models to improve prediction accuracy. However,many commonly used models(e.g., long short-term memory, LSTM) can only implicitly simulate memory effects, but lack effective mechanisms to capture memory effects from sequence data and estimate their effective time range(ETR). This shortage makes it hard to dynamically configure the most suitable length of used historical information according to the current driving behavior, which harms the good understanding of vehicle motion. To address this problem, we propose a modified trajectory prediction model based on ordered neuron LSTM(ON-LSTM). We demonstrate the feasibility of ETR estimation based on ON-LSTM and propose an ETR estimation method. We estimate the ETR of driving fluctuations and lane change operations on the NGSIM I-80 dataset. The experiment results prove that the proposed method can well capture the memory effects during trajectory prediction. Moreover, the estimated ETR values are in agreement with our intuitions.

关键词： driving behavior memory effect trajectory prediction historical information ON-LSTM

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A Quantum-Like Human Learning Optimization Algorithm 8th

A Quantum-Like Human Learning Optimization Algorithm

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Ling Huang, Yi Qian, Chaolin Kang, Xing Zhang, Anfa Pardalos, Panos M. Fei, Minrui Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China Sino-European School of Technology Shanghai University Shanghai200444 China Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida GainesvilleFL32611 United States

ISBN: (纸本)9789819602933

Human Learning Optimization (HLO) is a novel potential and promising meta-heuristic, which is developed based on a simplified human learning model. In recent years, the hypothesis that the human cognitive process obeys the laws of quantum rather than classical probability has been successfully used to explain a variety of seemingly "irrational" judgment and human decision-making behaviors, and the independent evidence for this hypothesis has been provided from different experiments. Inspired by this hypothesis, this paper introduces a quantum cognition model of humans into HLO and proposes a quantum-like human learning optimization algorithm (QHLO), in which the belief and its change in human brains during the learning process is simulated and implemented in the search of the algorithm. The developed QHLO is validated on the benchmark functions, and the performance is compared with one recent HLO variants, two quantum-inspired meta-heuristics and two recent binary meta-heuristics. The experimental results show that that the presented QHLO inherits the advantages of HLO and has better global search ability as its diversity is further enhanced with the integration of the quantum cognition model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

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An Improved Cooperative Team Spraying Control of a Diffusion Process With a Moving or Static Pollution Source

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 494-504页

作者： Juan Chen Baotong Cui Yang Quan Chen Bo Zhuang Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education)and School of IoT Engineering Jiangnan UniversityWuxi 214122China Mechatronics Embedded Systems and Automation LaboratoryUniversity of CaliforniaMerced CA 95343 USA

This paper is concerned with a control problem of a diffusion process with the help of static mesh sensor networks in a certain region of interest and a team of networked mobile actuators carrying chemical *** major contribution of this paper can be divided into three parts:the first is the construction of a cyber-physical system framework based on centroidal Voronoi tessellations(CVTs),the second is the convergence analysis of the actuators location,and the last is a novel proportional integral(PI)control method for actuator motion planning and neutralizing control(e.g.,spraying)of a diffusion process with a moving or static pollution source,which is more effective than a proportional(P)control *** optimal spraying control cost function is ***,the minimization problem of the spraying amount is ***,a new CVT algorithm based on the novel PI control method,henceforth called PI-CVT algorithm,is introduced together with the convergence analysis of the actuators location via a PI control ***,a modified simulation platform called diffusion-mobile-actuators-sensors-2-dimension-proportional integral derivative(Diff-MAS2D-PID)is *** addition,a numerical simulation example for the diffusion process is presented to verify the effectiveness of our proposed controllers.

关键词： Centroidal Voronoi tessellations(CVTs) diffusion processes mobile actuator-sensor networks(MAS-Net) PI control

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