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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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Guidance and Control of Underwater Hexapod Robot Based on Adaptive Sliding Mode Strategy

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Journal of Bionic engineering 2025年第1期22卷 118-132页

作者： Qingshuo Gong Wei Zhang Yu Su Haoyu Yang College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbin150001China

Animals exhibit remarkable mobility and adaptability to their *** these advantages,various types of robots have been *** achieve path tracking control for the underwater hexapod robot,a path tracking control system has been *** this system,a Line-of-Sight(LOS)guidance system is utilized to generate the desired heading angle during the path tracking process.A heading tracking controller and a speed tracking controller are designed based on the super-twisting sliding mode *** logic is employed to establish the nonlinear relationship between the output of the upper-level controller,which includes force/torque,and the input parameters of the Central Pattern Generator(CPG)***,the effectiveness of the proposed method is verified through simulation and *** results demonstrate that the robot exhibits good tracking accuracy,as well as stability and coordination in *** designed path tracking system enables the underwater hexapod robot to rapidly and accurately track the desired path.

关键词： Underwater hexapod robot Path tracking Sliding mode control

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Dynamic Event-Triggered Active Disturbance Rejection Formation Control for Constrained Underactuated AUVs

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 460-462页

作者： Zhiguang Feng Sibo Yao IEEE the College of Intelligent Systems Science and Engineering Harbin Engineering University

Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a nonlinear state dependence function (NSDF) that transforms the state of each AUV in the formation.

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Current Optimized Torque Sharing Function Control for Switched Reluctance Motor Based on Quasi-Proportional Resonance Controller

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年第2期13卷 1662-1672页

作者： He, Hai Yao, Xuliang Wang, Jingfang Zheng, Boyuan Guan, Qi Harbin Engineering University College of Intelligent Systems Science and Engineering Harbin150001 China

This article proposes a current optimized torque sharing function (TSF) control method with the quasi-proportional resonance (QPR) controller to reduce torque ripple and copper losses of switched reluctance motor (SRM). First, the SRM operating regions are divided based on the torque-current ratio, enabling a clearer distinction between the torque output capabilities of different phases. Then, considering the effect of inductance on the current in different regions and combined with the square root of the increment of inductance, a current optimized TSF control method is proposed. This method aims to fully utilize the torque output capabilities of different phases in different regions, thereby reducing the influence of current peak on copper losses and the torque ripple. Finally, considering the requirements of the periodically changing torque reference on the frequency gain and bandwidth of the torque controller, the QPR torque controller is applied to the SRM to reduce torque tracking error and improve the dynamic response of the system. Experiments are carried out on a three-phase 12/8 SRM to verify the effectiveness of the proposed TSF with QPR. © 2013 IEEE.

关键词： Reluctance motors

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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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Analysis and image encryption of memristive chaotic system with coexistence bubble

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Chinese Physics B 2025年第4期34卷 250-260页

作者： Da Qiu Bo Zhang Tingting Zhang Song Liu Peiyu He Sichuan University College of Electronics and Information EngineeringChengdu 610065China Hubei Minzu University School of Intelligent Systems Science and EngineeringEnshi 445000China

In recent years,the phenomenon of multistability has attracted wide *** this paper,a memristive chaotic system with extreme multistability is constructed by using a *** dynamic behavior of the system is analyzed by Poincar´e mapping,a time series diagram,and a bifurcation *** results show that the new system has several significant ***,the new system has a constant Lyapunov exponent,transient chaos and one complete Feigenbaum ***,the system has the phenomenon of bifurcation map shifts that depend on the initial *** addition,we find periodic bursting oscillations,chaotic bursting oscillations,and the transition of chaotic bursting oscillations to periodic bursting *** particular,when the system parameters take different discrete values,the system generates a bubble phenomenon that varies with the initial conditions,and this bubble can be shifted with the initial values,which has rarely been seen in the previous *** implementation by field-programmable gate array(FPGA)and analog circuit simulation show close alignment with the MATLAB numerical simulation results,validating the system’s ***,the image encryption algorithm integrating DNA-based encoding and chaotic systems further demonstrates its practical applicability.

关键词： coexistence bubble extreme multistability clustered oscillation anti-monotonicity

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Dynamic Regret for Distributed Online Composite Optimization

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IEEE Transactions on Automatic Control 2025年第5期70卷 3056-3071页

作者： Hou, Ruijie Yu, Yang Li, Xiuxian Tongji University Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai201800 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai Institute of Intelligent Science and Technology Shanghai201210 China

This article focuses on online composite optimization over multiagent networks. In the distributed setting, each agent has its own local loss function, which consists of a convex, strongly convex or strongly convex and smooth function, and a time-varying nonsmooth regularizer. Two distributed online algorithms are proposed and corresponding dynamic regrets are analyzed. Two proposed algorithms are based on signs of relative states. The first algorithm obtains (Formula presented) dynamic regret bound when each local loss is a general convex composite function, where CT is the path variation. If CT can be estimated in advance for convex or strongly convex local loss with a time-varying nonsmooth regularizer, then dynamic regret bounds are, respectively, in the order of (Formula presented) and o (log T(1 + CT)). The second algorithm is based on the first one, especially for handling the local loss composed of a strongly convex and smooth function with a nonsmooth regularizer, and then obtains o (1 + CT) dynamic regret bound. In the end, numerical results are given to support the theoretical findings. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Automatic Input Voltage Sharing of ISOP Converter Using Duty Ratio Feedforward Control Without Interconnection and Input Voltage Monitor

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IEEE Transactions on Power Electronics 2025年第8期40卷 11143-11156页

作者： Zhou, Wei You, Jiang Peng, Hui Zhang, Liuzhong College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China Yantai Research Institute Harbin Engineering University Yantai China

The input-series–output-parallel (ISOP) DC/DC converter is ideal for applications requiring high input voltage and large output current. Ensuring proper input voltage sharing across the different submodules on the series side is crucial for practical implementation in ISOP systems. This paper proposes a novel duty ratio feedforward control scheme that automatically balances the input voltage amongst the modules in the ISOP conversion system. In this method, each module operates independently without the need for interconnections to facilitate information exchange, and input voltage monitoring is unnecessary. Instead, only output voltage and filter inductor current need to be sampled, eliminating the requirement for high voltage isolation in conditioning circuits. Therefore, a fully modular design is achievable in the ISOP converter, improving metrics such as complexity, cost and reliability. This paper presents a detailed discussion of the principle, small-signal model-based stability analysis and control system design. Experimental results are presented to validate the effectiveness of the proposed control strategy. © 1986-2012 IEEE.

关键词： Feedforward control

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Distributed observer-based prescribed-time affine formation control for underactuated unmanned surface vessels under DoS attack

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ISA Transactions 2025年 159卷 165-180页

作者： Liu, Tao Li, Jixiang Zhou, Bin Hao, Yong Wang, Xianfeng College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin150001 China Science and Technology on Underwater Vehicle Laboratory Harbin Engineering University Harbin150001 China

This study addresses the control challenges of distributed prescribed-time maneuvers for underactuated unmanned surface vessels (USVs) operating in affine formation under adverse conditions, including ocean disturbances, unmodeled dynamics, and denial-of-service (DoS) attacks. The research develops a control scheme that enables USVs to perform complex maneuvers such as translation, shearing, rotation, and scaling, despite intermittent communication failures due to periodic DoS attacks. The approach integrates a distributed prescribed-time observer (DPTO) for each vessel to monitor local time-varying desired states, coupled with an adaptive prescribed-time local tracking control (APTLTC) strategy that drives the USV to track the desired states. The effectiveness and robustness of this control solution are validated through theoretical analysis and simulation, demonstrating significant resilience against network disruptions. This study contributes to safer maritime operations by providing a robust control framework for underactuated USVs under cyber-physical threats. © 2025

关键词： Denial-of-service attack

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A Robust Online Miscalibration Detection and Correction Method for LiDAR-Camera

A Robust Online Miscalibration Detection and Correction Meth...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Pan, Feng Wang, Wei Zhang, Jianing College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798350368741

The increasing reliance on multi-sensor systems to enhance the robustness and accuracy of robotic systems introduces new challenges, particularly in calibrating multiple sensors. Traditional offline calibration techniques, which use targets like checkerboards, assume that extrinsic parameters between sensors remain constant during operation. However, this assumption does not account for drift caused by external factors such as vibration and deformation over time. In this letter, we introduce CalibOnline, a novel method for the online detection and correction of miscalibration in multi-sensor setups. First, we propose a unified representation of LiDAR and camera data as depth maps to reduce calibration uncertainties due to data modality discrepancies. We then explore the robust characteristic of depth discontinuity edges to facilitate efficient matching between depth maps. The impact of extrinsic variations on edge-matching constraints is analyzed, leading to the design of a miscalibration detection module to monitor extrinsic parameters. Finally, we frame the correction of extrinsic parameters as an on-manifold optimization problem, enhancing the convergence of the estimated parameters. Experimental results across various scenarios demonstrate the robustness and accuracy of our proposed method. Code is open-sourced at: https://***/cchester25/***. © 2025 IEEE.

关键词： calibration miscalibration correction miscalibration detection on-manifold optimization

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