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American control Conference (ACC)

作者： Wenpeng Wei Guodong Yin Jinxiang Wang Tianyi He School of Mechanical Engineering Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Department of Mechanical and Aerospace Engineering Utah State University Logan USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper proposes a moving-window Integrated Physics-Data-Based (IPDB) modeling method for the lateral dynamics of autonomous vehicles. The IPDB modeling method initiates from the fundamental physical principles of vehicle motions and express the nonlinear lateral dynamics directly by data snapshots in a moving window. Therefore, the IPDB model is physically interpretable and inherits adaptiveness of data-driven approaches. Specifically, the physics-based lateral dynamics are expressed into affine linear parameter-varying (LPV) formulation and system matrices can be successfully represented by the data snapshots in finite-length moving window without training or calibrations. After that, the CarSim simulations are conducted for data collection and to derive IPDB model. The data-efficient and online adaptive characteristics are validated by the data under several driving scenes. Simulation results confirm that the moving-window IPDB model only uses a small amount of data, but can exhibit great online modeling capability with strong adaptation and excellent model accuracy under varying driving scenarios.

关键词： Training Adaptation models Accuracy Computational modeling Dynamics Data models Mathematical models

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Symplectic Space Wave Propagation Method for Forced Vibration of Acoustic Black Hole Assemblies

SSRN

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SSRN 2023年

作者： Zhang, Sen Ma, Yongbin Yan, Meng Deng, Zichen School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi’an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China

A symplectic space wave propagation method is proposed for the forced vibration of the Acoustic Black Hole (ABH) assemblies. The governing differential equations for vibration of the ABH beam is first converted into Hamiltonian canonical equations. A symplectic eigenvalue problem is then formed, and the wave propagation parameters and wave shapes are obtained analytically. Secondly, A Gaussian point scheme is subsequently used to discrete the ABH beam, while the presented method is used to evaluate the wave amplitude at each point. Various coupling forms are considered for the ABH assemblies, in which the ABH beams are coupled directly or through a joint. The wave propagation method based on symplectic analysis is used to describe the vibration of ABH beams and the finite element method is used to describe the vibration of the joint. By using the displacement continuity and equilibrium of force at the connection interface, the dynamic coupling between the ABH beam and the joint is established. Since the presented method utilizes symplectic analytical solutions of wave modes, the computational efficiency and precision are high that are verified by several numerical examples. © 2023, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Bayesian Exponential Regularized Tensor Based Approach for Sparse Geomagnetic Data Completion

Bayesian Exponential Regularized Tensor Based Approach for S...

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Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Guoyu Li Junchi Bin Huan Liu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Wuhan China School of Engineering University of British Columbia Okanagan BC Canada

Geomagnetic data is vital for predicting earthquakes and magnetic storms. In this regard, a new Bayesian exponential regularized tensor completion framework for sparse geomagnetic data, i.e. BERTC, is proposed to address this problem in the study. First, the spatiotemporal geomagnetic data is reshaped into a 3D tensor with days and hours that features random missing elements. Second, a Gibbs sampling algorithm is developed to achieve probabilistic inference on matrices' factors and corresponding parameters in this model. Thus, the sparse tensor can be gradually optimized to fill the missing entries during iterations. Third, an exponential regularizer is proposed to reduce oscillations before and after iterations to enhance imputation quality further. Finally, the derived factor matrices are aggregated from Gibbs sampling to complete the sparse tensor. Numerical geomagnetic datasets from 13 cities are employed, and extensive comparison experiments are conducted to evaluate the imputation performance of the BERTC. The results show the superiority of the proposed BERTC compared to the state-of-the-art methods in terms of imputation accuracy, with an approximate improvement of the imputation accuracy as no less than 20%.

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Kirigami-inspired rigid-foldable meta-structure with a bidirectional self-locking property

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Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 2025年第2315期481卷

作者： Li, Jihui An, Siqi Wu, Xinwei Deng, Dongxuan Deng, Zichen School of Mechanics Civil Engineering and Architecture MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an710072 China Department of Engineering Mechanics Zhejiang University Hangzhou310027 China School of Information Mechanics and Sensing Engineering Xidian University Xi'an710071 China

Self-locking is an attractive feature in origami structures that enables the foldable structure to withstand loads along the direction of deployment, without requiring extra locking elements. However, this feature is rarely observed in rigid origami because such structures can be easily folded or deployed along the deployment direction. Here, we introduce a novel origami meta-structure with both rigid foldability and bidirectional self-locking capacity based on a kirigami-inspired foldable icosahedron. The kinematic analysis demonstrates that a foldable icosahedron has two motion steps separated by a bifurcation point. By stacking two icosahedra together, we construct a rigid-foldable module capable of bearing both tensile and compressive loads along the direction of deployment. Through energy analysis and prototype experiments, we demonstrate that the bidirectional self-locking phenomenon originates from both the multiple motion steps of a foldable icosahedron and the torsional stiffness of creases. We arrange the module into a planar array and show its potential application in mechanical memory storage devices. This work paves a new way to design rigid-foldable and bidirectional self-locking origami structures. © 2025 The Author(s).

关键词： Digital arithmetic

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Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance

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Frontiers of Information Technology & Electronic Engineering 2021年第7期22卷 986-1001页

作者： Xuerao WANG Qingling WANG Changyin SUN School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China

In this paper,an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation.A novel finite-time neural network disturbance observer is constructed to estimate the system uncertainties and external *** guarantee the prescribed performance,an error transformation is applied to transfer the time-varying constraints into a constant ***,by employing a barrier Lyapunov function and the backstepping technique,an observer-based tracking control strategy is *** is proven that using the proposed algorithm,all the closedloop signals are bounded,and the tracking errors satisfy the predefined time-varying performance ***,simulation results on a quadrotor system are given to illustrate the effectiveness of the proposed control scheme.

关键词： Adaptive tracking control Prescribed performance Input saturation Disturbance observer Neural network

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Double wavelet threshold filter design for real-time adaptive denoising in OA-ICOS

Double wavelet threshold filter design for real-time adaptiv...

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Jiangsu Annual Conference on Automation (JACA 2024)

作者： Yixin Deng Zairan Wang Yang-Yang Chen Qin Liu Xiangyu Wang School of Automation and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing People's Republic of China School of Cyber Science and Engineering Southeast University Nanjing People's Republic of China

ISBN: (数字)9781837242719

In the Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) technique, single-stage filters are commonly used to reduce noise and improve the signal-to-noise ratio, enabling more precise CO2 concentration detection. However, these filters often underperform under real-time conditions. To enhance real-time performance, this paper proposes a novel framework based on Double Wavelet Threshold Filter (DWTF) that adaptively suppresses noise while preserving key features of CO2 concentration signal. Firstly, one wavelet threshold filter (WT) is introduced to calculate the mean of the current sequence, providing an initial denoising step. Secondly, another WT is employed to extract features from a longer sequence for adaptive computation of the discount factor. Finally, an exponential moving average filter (EMA) is applied to combine both current and historical data to produce a smoother aggregated output. To validate the effectiveness, DWTF was compared with other conventional algorithms for a CO2 dataset with three distinct states: smooth, ship and mutant, obtained by OA-ICOS. The experimental results demonstrate that DWTF performs effectively in all three states.

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Feature-Prescribed Iterative Learning control of Waggle Dance Movement for Social Motor Coordination in Joint Actions

arXiv

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arXiv 2024年

作者： Guo, Bowen Zhai, Chao School of Automation China University of Geosciences Wuhan430074 China 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

Extensive experiments suggest that motor coordination among human participants may contribute to social affinity and emotional attachment, which has great potential in the clinical treatment of social disorders or schizophrenia. Mirror game provides an effective experimental paradigm for studying social motor coordination. Nevertheless, the lack of movement richness prevents the emergence of high-level coordination in the existing one-dimensional experiments. To tackle this problem, this work develops a two-dimensional experimental paradigm of mirror game by playing waggle dance between two participants. In particular, an online control architecture of customized virtual player is created to coordinate with human player. Therein, an iterative learning control algorithm is proposed by integrating position tracking and behavior imitation with prescribed kinematic feature. Moreover, convergence analysis of control algorithm is conducted to guarantee the online performance of virtual player. Finally, the proposed control strategy is validated by matching experimental data and compared with other control methods using a set of performance indexes. Copyright © 2024, The Authors. All rights reserved.

关键词： Mirrors

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Game-theoretical explorations of the mesoscale flow structure and regime transitions in bubble columns

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Particuology 2020年第1期18卷 100-108页

作者： Shuo Yuan Yifen Mu Xiaoping Guan Zhixin Liu Jianhua Chen Ning Yang Lin Zhang Key Lab of Systems and Control Institute of Systems SciencesAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China

Understanding the mesoscale structure and regime transition in bubble columns is of great significance for reactor design and *** on the energy-minimization multiscale(EMMS)model,a noncooperative game model with constraints is proposed to investigate the structural properties of gas-liquid systems in which small and large bubbles are chosen as players and the energy consumption form the objective *** conservation equations of the system can be regarded as the constraints of the *** the formulated noncooperative game model,the concept of the generalized Nash equilibrium(GNE)is used to characterize the *** algorithm is developed to numerically compute the GNE and some important structural parameters in the *** numerical results show the existence of the GNE for all values of the superficial gas velocity *** Ug varies,the trends in the state variables can be observed and the critical point of Ug *** overall trend of the flow regime transition agrees with the original EMMS model and experimental results,although the GNE calculation also reveals different single-bubble dominant mechanisms with increasing Ug.

关键词： Bubble column Mesoscale Regime transition Game theory Generalized Nash equilibrium EMMS model

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Formulation of optimization Problems with Radiation Field Phases as Design Variables for Pattern Synthesis of Linear Antenna Arrays

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China Communications 2022年第12期19卷 86-100页

作者： Fei Zhao Jun He Sanyou Zeng Changhe Li Qinghui Xu Zhigao Zeng School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China Science and Technology on Blind Signal Processing Laboratory Southwest Electronics and Telecommunication Technology Research InstituteChengdu 610041China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China College of Computer Hunan University of TechnologyZhuzhou CityHunan Province412007China

Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of optimization *** new optimization formulation has two differences from the common *** is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the *** difference is beneficial to decrease complexity in some *** second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation *** difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are *** results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.

关键词： pattern synthesis evolutionary algorithms linear antenna arrays

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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