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An Online Exploratory Maximum Likelihood Estimation Approach to Adaptive Kalman Filtering

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 228-254页

作者： Jiajun Cheng Haonan Chen Zhirui Xue Yulong Huang Yonggang Zhang the College of Intelligent Systems Science and Engineering Harbin Engineering University the Engineering Research Center of Navigation Instruments Ministry of Education the College of Intelligent Systems Science and Engineering the College of Future Technology Harbin Engineering University IEEE

Over the past few decades, numerous adaptive Kalman filters(AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is challenging, especially when both the process noise and measurement noise covariance matrices are relatively inaccurate. Maximum likelihood estimation(MLE) possesses the potential to achieve this goal, since its theoretical accuracy is guaranteed by asymptotic optimality and the convergence speed is fast due to weak dependence on accurate state ***, the maximum likelihood cost function is so intricate that the existing MLE methods can only simply ignore all historical measurement information to achieve online estimation,which cannot adequately realize the potential of MLE. In order to design online MLE-based AKFs with high estimation accuracy and fast convergence speed, an online exploratory MLE approach is proposed, based on which a mini-batch coordinate descent noise covariance matrix estimation framework is developed. In this framework, the maximum likelihood cost function is simplified for online estimation with fewer and simpler terms which are selected in a mini-batch and calculated with a backtracking method. This maximum likelihood cost function is sidestepped and solved by exploring possible estimated noise covariance matrices adaptively while the historical measurement information is adequately utilized. Furthermore, four specific algorithms are derived under this framework to meet different practical requirements in terms of convergence speed, estimation accuracy,and calculation load. Abundant simulations and experiments are carried out to verify the validity and superiority of the proposed algorithms as compared with existing state-of-the-art AKFs.

关键词： Adaptive Kalman filtering coordinate descent maximum likelihood estimation mini-batch optimization unknown noise covariance matrix

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Attar: RRAM-based in-memory attention accelerator with software-hardware co-optimization

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Science China(Information Sciences) 2025年第3期68卷 371-387页

作者： Bing LI Ying QI Ying WANG Yinhe HAN Information Engineering College Capital Normal University Research Center for Intelligent Computing Systems Institute of Computing TechnologyChinese Academy of Sciences

The attention mechanism has become a pivotal component in artificial intelligence, significantly enhancing the performance of deep learning applications. However, its quadratic computational complexity and intricate computations lead to substantial inefficiencies when processing long sequences. To address these challenges, we introduce Attar, a resistive random access memory(RRAM)-based in-memory accelerator designed to optimize attention mechanisms through software-hardware co-optimization. Attar leverages efficient Top-k pruning and quantization strategies to exploit the sparsity and redundancy of attention matrices, and incorporates an RRAM-based in-memory softmax engine by harnessing the versatility of the RRAM crossbar. Comprehensive evaluations demonstrate that Attar achieves a performance improvement of up to 4.88× and energy saving of 55.38% over previous computing-in-memory(CIM)-based accelerators across various models and datasets while maintaining comparable accuracy. This work underscores the potential of in-memory computing to enhance the efficiency of attention-based models without compromising their effectiveness.

关键词： RRAM computing-in-memory attention pruning quantization

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Stability and Stabilization of Sampled-Data Based LFC for Power systems:A Data-Driven Method

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 291-293页

作者： Yu-Long Fan Chuan-Ke Zhang Yong He the School of Automation China University of Geosciences the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词： Sampled data control systems

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 723-733页

作者： Xiongbo Wan Chaoling Zhang Fan Wei Chuan-Ke Zhang Min Wu IEEE the School of Automation China University of Geosciencesthe Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systemsand the Engineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationWuhan 430074China

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic *** addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI *** the designed controller,the involved fuzzy system is ensured to be asymptotically *** examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

关键词： Dynamic event-triggered mechanism(DETM) hybrid dynamic variables model predictive control(MPC) robust positive invariant(RPI)set T-S fuzzy systems

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Fixed-time stabilization of discontinuous spatiotemporal neural networks with time-varying coefficients via aperiodically switching control

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Science China(Information Sciences) 2023年第5期66卷 182-195页

作者： Xiaofang HU Leimin WANG Chuan-Ke ZHANG Xiongbo WAN Yong HE School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which facilitates the handling of time-varying coefficients of SNNs and relaxes the restriction on the non-positive definiteness of the derivative of the Lyapunov function. Besides, a more flexible and economical aperiodically switching control technique is presented to stabilize SNNs within a fixed time,efectively reducing the amount of information transmission and control costs. Under the newly established fixed-time convergence lemma and aperiodically switching controller, many more general algebraic conditions are deduced to ensure the fixed-time stabilization of SNNs. Numerical examples are provided to manifest the validity of the results.

关键词： spatiotemporal neural networks discontinuous activations time-varying coefficients fixed-time stabilization aperiodically switching control

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Effect of post rolling stress on phase transformation behavior of microalloyed dual phase steel

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Journal of Iron and Steel research International 2024年第3期31卷 688-699页

作者： Wen-quan Sun Sheng-yi Yong Tie-heng Yuan Ting-song Yang An-rui He Chao Liu Rui-chun Guo National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing University of Science and Technology BeijingBeijing 100083China

The slow phase transformation of microalloyed dual phase steel makes the nonuniform stress and temperature fields during the post rolling cooling process have a significant impact on the phase transformation *** the relatively slow phase transformation of DP780 steel within the microalloyed dual phase steel series,the influence of stress on the phase transformation behavior of DP780 steel was *** quantify the nonuniform thermal and stress conditions in the steel coil,a thermo-mechanical coupled finite element model of the hot-rolled strip cooling process was *** on the simulation data,DP780 steel was chosen as the research material,and Gleeble 3500 thermal simulation equipment was used for experimental *** thermal expansion curves were analyzed through regression to establish the dynamic model of DP780 steel phase transformation under ***,metallographic analysis was conducted to determine phase transformation type and grain size of DP780 *** results confirmed that the stress promotes the occurrence of semi-diffusion-type bainite ***,an appropriate level of stress facilitates the growth of bainitic grains,while the increased stress inhibits the growth of ferritic grains.

关键词： Microalloyed dual phase steel Stress Bainitic transformation Grain Finite element method

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Recent advances in photopolymerization 3D printing of alumina-ceramic

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Progress in Natural Science:Materials International 2025年第1期35卷 1-30页

作者： M.Irfan Hussain Min Xia XiaoNa Ren Zhen Shen Muhammad Jamil Changchun Ge Institute of Powder Metallurgy and Advanced Ceramics School of Material Science and Engineering University of Science and Technology Beijing State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics

Digital light processing(DLP) 3D printing has a huge potential for manufacturing intricate and customized ceramic parts with high precision and cost-effectiveness. research in this field contributes to material innovation,opening the avenues for new process designs in both scientific and industrial sectors. However, the implementation of DLP 3D printing technology in ceramic research has not yet reached the maturity level as that in polymer and tissue engineering. Necessarily, a holistic in-depth literature reporting the successful integration of alumina ceramics within DLP 3D printing technology is urgently needed. This review, systematic examines recent progress in DLP technology, focusing on photopolymer resins that incorporate UV-sensitive monomers, photoinitiators, and dispersants, as well as their synergistic effects on achieving high-quality printing, desirable material properties, and enhanced performance. Further, the review discusses key factors including post-processing characteristics such as debinding and sintering, which influence microstructure, and defect formation including microcracks, porosity and voids. Finally, the challenges associated with printing and sintering are highlighted,aiming to identify focused focused development pathways and potential solution to optimize outcomes. This analysis clarifies existing challenges and also propsoes future applications for DLP technology in the aluminaceramic field.

关键词： Al2O3 ceramics Applications Digital light processing (DLP) Post-processing Resin

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Enhancing rheology and mechanical properties of DLP 3D-printed Si_(3)N_(4) materials via composition optimization and gas-pressure sintering

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International Journal of Minerals,Metallurgy and Materials 2025年第5期32卷 1220-1233页

作者： Qing Qin Gang Xiong Lin Han Yujuan Zhang Zhen Shen Changchun Ge Institute of Powder Metallurgy and Advanced Ceramics School of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and TechnologyInstitute of AutomationChinese Academy of SciencesBeijing 100190China

Digital light processing(DLP)is a crucial additive manufacturing(AM)technique for producing high-precision ceramic *** study aims to optimize the formulation of Si_(3)N_(4)slurry to enhance both its performance and manufacturability in the DLP process,and investigate key factors such as particle size distribution,photopolymer resin monomer ratios,and dispersant types to im-prove the slurry’s rheological *** these optimizations,a photosensitive Si_(3)N_(4)slurry with 50vol%solid content was de-veloped,exhibiting excellent stability,and low viscosity(2.48 Pa·s at a shear rate of 12.8 s^(-1)).The effects of gas-pressure sintering on the material’s phase composition,microstructure,and mechanical properties were further explored,revealing that this technique significantly increases the flexural strength of the green sample from(109±10.24)to(618±42.15)*** sintered ceramics exhibited high hard-ness((16.59±0.05)GPa)and improved fracture toughness((4.45±0.03)MPa·m^(1/2)).Crack trajectory analysis revealed that crack deflec-tion,crack bridging,and the pull-out of rod-likeβ-Si_(3)N_(4)grains,are the main toughening mechanisms,which could effectively mitigate crack *** these mechanisms,crack deflection and bridging were particularly influential,significantly enhancing the frac-ture toughness of the Si_(3)N_(4)***,this research highlights how monomer formulation and gas-pressure sintering strengthen the performance of Si_(3)N_(4)slurry in the DLP three-dimensional printing *** work is expected to provide new insights for fabricat-ing complex Si_(3)N_(4)ceramic components with superior mechanical properties.

关键词： additive manufacturing Si_(3)N_(4)slurry low viscosity pressure sintering

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Enhancing Robot Arm Trajectory Tracking through Reinforcement Learning based Compensation 4

Enhancing Robot Arm Trajectory Tracking through Reinforcemen...

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4th International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Sun, Chenwei Ovtcharova, Jivka Intelligent Systems and Production Engineering FZI Research Center for Information Technology Karlsruhe Germany

ISBN: (纸本)9798350391183

This paper proposes a reinforcement learning (RL) based compensator for minimising the trajectory tracking deviation of a robot arm under external disturbances. The compensator adaptively incorporates the weighted joint position errors into the reference joint position values, with the weighting factor provided by the RL action output. The effectiveness of the method has been verified on a simulated robot model with realistic physical properties in Gazebo simulator. The focus of this study is on evaluating the linear tracking performance of the robot under both sinusoidal and constant forces applied to the its end-effector. The experiment results show that the proposed method can reduce the mean tool center point (TCP) trajectory deviation over 44%. The result also demonstrate the feasibility of compensation without requiring the TCP position information, using only the robot joint information, offering a more cost-efficient solution. © 2024 IEEE.

关键词： Reinforcement learning

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