Control and Optimization, Control and Systems Engineering, Artificial Intelligence
32
Scopus Publications
350
Scholar Citations
10
Scholar h-index
10
Scholar i10-index
Scopus Publications
A combined feature selection approach for malicious email detection based on a comprehensive email dataset Han Zhang, Yong Shi, Ming Liu, Libo Chen, Songyang Wu, Zhi Xue Cybersecurity, 2025 In recent years, new malicious email attacks have emerged. We summarize two major challenges in the current field of malicious email detection using machine learning algorithms. (1) Current works on malicious email detection use different datasets and lack a unified and comprehensive open source dataset standard for evaluating detection performance. In addition, outdated data makes it difficult to detect new types of malicious email attacks. (2) There are limitations in feature selection and extraction. Relying only on static features or body textual features cannot satisfy the detection of both common phishing or spam email and new malicious emails that exploit protocol vulnerabilities. To address these problems, we propose the Exploiting Protocol Vulnerability Malicious Email (EPVME) dataset, which contains 49,136 malicious email samples. The EPVME dataset is constructed by summarizing and simulating the novel types of malicious email attacks that exploit email protocol vulnerabilities. In our dataset, the coverage of the types of malicious emails and the number of them are significantly increased. By collecting the currently available open source datasets, we build a large-scale dataset with 660,985 samples. Through two sets of comparative experiments on the dataset containing EPVME, we verify the necessity, reliability, and validity of the EPVME dataset. By using a large and comprehensive open source email dataset, we hope to help subsequent work on malicious email detection achieve comparative performance. Furthermore, we propose a new feature selection and construction method that combines both static features and textual features. We extract 79 static features from both the header and body parts of email samples, perform textual feature extraction on the pre-processed body parts, and combine various machine learning algorithms for detection model construction and experimental comparison. Our detection model can achieve an accuracy of 99.968% and a false positive rate of 0.099%.
Error Dynamics in Affine Group Systems Xinghan Li, Jianqi Chen, Han Zhang, Jieqiang Wei, Junfeng Wu IEEE Transactions on Automatic Control, 2025 Error dynamics captures the evolution of state errors between two distinct trajectories that are governed by the same dynamical system rule but initiated and/or perturbed differently. It is essential to analyze the error behavior of a state observer on a matrix Lie group for precise estimation. This article concentrates on the examination of error dynamics in affine group systems when exposed to external disturbances or random noises. To this end, we first characterize linear group systems equivalently by homomorphism of its transition flow and linearity of its Lie algebra. Next, we investigate linear group systems that are spread by a Brownian motion in tangent spaces. We show that the Itô stochastic differential equation in the Lie algebra space has a linear drift component and an additional “pinning” term. We apply these findings in analyzing error dynamics, a specific linear group system, with smooth disturbances and random noises. The error dynamics is expressed in the group and the Lie algebra. An explicit and accurate derivation of error dynamics is provided for a concrete example of $SE_{2}(3)$, which plays a vital role in inertial-based navigation and other robotics applications.
Optimization-Based Trajectory Planning for Tractor-Trailer Vehicles on Curvy Roads: A Progressively Increasing Sampling Number Method Zehao Wang, Han Zhang, Jingchuan Wang, Weidong Chen IEEE Transactions on Intelligent Transportation Systems, 2025 In this work, we propose an optimization-based trajectory planner for tractor-trailer vehicles on curvy roads. The lack of analytical expression for the trailer's errors to the center line pose a great challenge to the trajectory planning for tractor-trailer vehicles. To address this issue, we first use geometric representations to characterize the lateral and orientation errors in Cartesian frame, where the errors would serve as the components of the cost function and the road edge constraints within our optimization process. Next, we generate a coarse trajectory to warm-start the subsequent optimization problems. On the other hand, to achieve a good approximation of the continuous-time kinematics, optimization-based methods usually discretize the kinematics with a large sampling number. This leads to an increase in the number of the variables and constraints, thus making the optimization problem difficult to solve. To address this issue, we design a Progressively Increasing Sampling Number Optimization (PISNO) framework. More specifically, we first find a nearly feasible trajectory with a small sampling number to warm-start the optimization process. Then, the sampling number is progressively increased, and the corresponding intermediate Optimal Control Problem (OCP) is solved in each iteration. Next, we further resample the obtained solution into a finer sampling period, and then use it to warm-start the intermediate OCP in next iteration. This process is repeated until reaching a threshold sampling number. Simulation and experiment results show the proposed method exhibits a good performance and less computational consumption over the benchmarks.
A 4D Radar Camera Extrinsic Calibration Tool Based on 3D Uncertainty Perspective N Points Chuan Cao, Xiaoning Wang, Wenqian Xi, Han Zhang, Weidong Chen, Jingchuan Wang IEEE International Conference on Intelligent Robots and Systems, 2025 4D imaging radar is a type of low-cost millimeter-wave radar(costing merely 10-20% of lidar systems) capable of providing range, azimuth, elevation, and Doppler velocity information. Accurate extrinsic calibration between millimeter-wave radar and camera systems is critical for robust multimodal perception in robotics, yet remains challenging due to inherent sensor noise characteristics and complex error propagation. This paper presents a systematic calibration framework to address critical challenges through a spatial 3d uncertainty-aware PnP algorithm (3DUPnP) that explicitly models spherical coordinate noise propagation in radar measurements, then compensating for non-zero error expectations during coordinate transformations. Finally, experimental validation demonstrates significant performance improvements over state-of-the-art CPnP baseline, including improved consistency in simulations and enhanced precision in physical experiments. This study provides a robust calibration solution for robotic systems equipped with millimeter-wave radar and cameras, tailored specifically for autonomous driving and robotic perception applications.
Statistically consistent inverse optimal control for discrete-time indefinite linear–quadratic systems Han Zhang, Axel Ringh Automatica, 2024 The Inverse Optimal Control (IOC) problem is a structured system identification problem that aims to identify the underlying objective function based on observed optimal trajectories. This provides a data-driven way to model experts’ behavior. In this paper, we consider the case of discrete-time finite-horizon linear–quadratic problems where: the quadratic cost term in the objective is not necessarily positive semi-definite; the planning horizon is a random variable; we have both process noise and observation noise; the dynamics can have a drift term; and where we can have a linear cost term in the objective. In this setting, we first formulate the necessary and sufficient conditions for when the forward optimal control problem is solvable. Next, we show that the corresponding IOC problem is identifiable. Using the conditions for existence of an optimum of the forward problem, we then formulate an estimator for the parameters in the objective function of the forward problem as the globally optimal solution to a convex optimization problem, and prove that the estimator is statistical consistent. Finally, the performance of the algorithm is demonstrated on two numerical examples.
Visual Servoing of Flexible Manipulators With Unknown Camera Intrinsic Parameters and Vibration States Kai Li, Fan Xu, Han Zhang, Hesheng Wang IEEE ASME Transactions on Mechatronics, 2024 This article studies the visual servoing and vibration suppression of flexible manipulators using a fixed camera with uncalibrated intrinsic parameters. The dynamic equations of the flexible manipulator are decomposed into the slow and fast subsystems based on the singular perturbation theory. In the slow subsystem, the adaptive visual servoing controller is designed to regulate the positions of feature points on the image plane, where the unknown camera intrinsic parameters are estimated online. With respect to the fast subsystem, the unknown camera intrinsic parameters are regarded as the additional states of the fast subsystem, and the nonlinear state observer based on the Lie derivatives is developed to estimate the vibration states and camera parameters simultaneously from the visual feedback. The vision-based fast subsystem controller is proposed by using the estimated states to suppress the elastic vibration of the flexible manipulator. Both the stabilities of the slow and fast subsystems are proved based on the Lyapunov theory. Experimental results are provided to verify the effectiveness of the proposed control scheme.
Nonlinear Observer-Based Visual Servoing and Vibration Control of Flexible Robotic Manipulators with a Fixed Camera Kai Li, Han Zhang, Hesheng Wang IEEE Transactions on Cybernetics, 2024 This article studies the visual servoing and vibration suppression control for flexible manipulators when the system states are unmeasurable and only the image feedback is available. The dynamic equations of flexible manipulators are decomposed into the slow and fast subsystems based on the singular perturbation theory. The nonlinear observers based on the state transformation using the Lie derivatives are proposed to estimate the unmeasurable system states and unknown camera intrinsic parameters at the same time. Then, the image-based controllers utilizing the estimated states are, respectively, designed in the slow and fast subsystems to regulate the image positions of feature points and suppress the vibration of flexible manipulators simultaneously. In the proposed approach, only the visual feedback is required to generate the control input for flexible manipulators, which simplifies the controller implementation. The stability of the proposed control scheme is proved based on the Lyapunov theory. Finally, experimental results on a flexible single-link manipulator are provided to demonstrate the effectiveness of the proposed control approach.
U-OBCA: Uncertainty-Aware Optimization-Based Collision Avoidance via Wasserstein Distributionally Robust Chance Constraints Z Wang, Y Tang, H Zhang, J Wang, W Chen arXiv preprint arXiv:2603.04914 , 2026 2026
Consistent inverse optimal control for infinite time-horizon discounted nonlinear systems under noisy observations Z Wang, A Ringh, H Zhang arXiv preprint arXiv:2602.07874 , 2026 2026
Consistent inverse optimal control for discrete-time nonlinear stochastic systems Z Wang, H Zhang, A Ringh arXiv preprint arXiv:2511.22579 , 2025 2025 Citations: 1
A 4D Radar Camera Extrinsic Calibration Tool Based on 3D Uncertainty Perspective N Points C Cao, X Wang, W Xi, H Zhang, W Chen, J Wang 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems … , 2025 2025 Citations: 1
Design and Koopman Model Predictive Control of A Soft Exoskeleton Based on Origami-Inspired Pneumatic Actuator for Knee Rehabilitation J Wang, H Zhang, Z Wang, H Chen, P Wang, W Chen arXiv preprint arXiv:2510.11094 , 2025 2025
Terrain-Awared LiDAR-Inertial Odometry for Legged-Wheel Robots Based on Radial Basis Function Approximation Y Liu, H Zhang arXiv preprint arXiv:2509.26222 , 2025 2025
Registering the 4D Millimeter Wave Radar Point Clouds Via Generalized Method of Moments X Li, H Zhang, Z Wang, Y Yang, W Chen arXiv preprint arXiv:2508.02187 , 2025 2025
Optimization-based trajectory planning for tractor-trailer vehicles on curvy roads: A progressively increasing sampling number method Z Wang, H Zhang, J Wang, W Chen IEEE Transactions on Intelligent Transportation Systems , 2025 2025 Citations: 3
Recursive identification of nonlinear nonparametric systems under event-triggered observations X Ren, W Zhao, H Zhang Systems & Control Letters 196, 106013 , 2025 2025
Error Dynamics in Affine Group Systems X Li, J Chen, H Zhang, J Wei, J Wu IEEE Transactions on Automatic Control 70 (4), 2607-2614 , 2024 2024 Citations: 6
Statistically consistent inverse optimal control for discrete-time indefinite linear–quadratic systems H Zhang, A Ringh Automatica 166, 111705 , 2024 2024 Citations: 13
A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive Control G Yu, H Zhang, Z Wang, J Wang 2024 IEEE International Conference on Real-time Computing and Robotics (RCAR … , 2024 2024
K-bmpc: Derivative-based koopman bilinear model predictive control for tractor-trailer trajectory tracking with unknown parameters Z Wang, H Zhang, J Wang 2024 IEEE International Conference on Robotics and Automation (ICRA), 5808-5813 , 2024 2024 Citations: 7
Inverse optimal control for averaged cost per stage linear quadratic regulators H Zhang, A Ringh Systems & Control Letters 183, 105658 , 2024 2024 Citations: 13
Identifying Tracking Motion Pattern in Rehabilitation Using Inverse Optimal Control W Jiang, H Zhang, Z Wang 2023 China Automation Congress (CAC), 8399-8404 , 2023 2023
Nonlinear observer-based visual servoing and vibration control of flexible robotic manipulators with a fixed camera K Li, H Zhang, H Wang ieee Transactions on Cybernetics 54 (7), 4100-4110 , 2023 2023 Citations: 23
Visual servoing of flexible manipulators with unknown camera intrinsic parameters and vibration states K Li, F Xu, H Zhang, H Wang IEEE/ASME Transactions on Mechatronics 29 (1), 510-520 , 2023 2023 Citations: 9
4d radar-based pose graph slam with ego-velocity pre-integration factor X Li, H Zhang, W Chen IEEE Robotics and Automation Letters 8 (8), 5124-5131 , 2023 2023 Citations: 76
Inverse linear-quadratic discrete-time finite-horizon optimal control for indistinguishable homogeneous agents: A convex optimization approach H Zhang, A Ringh Automatica 148, 110758 , 2023 2023 Citations: 20
Statistically consistent inverse optimal control for linear-quadratic tracking with random time horizon H Zhang, A Ringh, W Jiang, S Li, X Hu 2022 41st Chinese Control Conference (CCC), 1515-1522 , 2022 2022 Citations: 11
MOST CITED SCHOLAR PUBLICATIONS
Inverse optimal control for discrete-time finite-horizon linear quadratic regulators H Zhang, J Umenberger, X Hu Automatica 110, 108593 , 2019 2019 Citations: 77
4d radar-based pose graph slam with ego-velocity pre-integration factor X Li, H Zhang, W Chen IEEE Robotics and Automation Letters 8 (8), 5124-5131 , 2023 2023 Citations: 76
Consensus control for linear systems with optimal energy cost H Zhang, X Hu Automatica 93, 83-91 , 2018 2018 Citations: 35
Inverse optimal control for finite-horizon discrete-time linear quadratic regulator under noisy output H Zhang, Y Li, X Hu 2019 IEEE 58th conference on decision and control (CDC), 6663-6668 , 2019 2019 Citations: 25
Nonlinear observer-based visual servoing and vibration control of flexible robotic manipulators with a fixed camera K Li, H Zhang, H Wang ieee Transactions on Cybernetics 54 (7), 4100-4110 , 2023 2023 Citations: 23
Inverse linear-quadratic discrete-time finite-horizon optimal control for indistinguishable homogeneous agents: A convex optimization approach H Zhang, A Ringh Automatica 148, 110758 , 2023 2023 Citations: 20
Statistically consistent inverse optimal control for discrete-time indefinite linear–quadratic systems H Zhang, A Ringh Automatica 166, 111705 , 2024 2024 Citations: 13
Inverse optimal control for averaged cost per stage linear quadratic regulators H Zhang, A Ringh Systems & Control Letters 183, 105658 , 2024 2024 Citations: 13
Projected primal–dual gradient flow of augmented Lagrangian with application to distributed maximization of the algebraic connectivity of a network H Zhang, J Wei, P Yi, X Hu Automatica 98, 34-41 , 2018 2018 Citations: 13
Statistically consistent inverse optimal control for linear-quadratic tracking with random time horizon H Zhang, A Ringh, W Jiang, S Li, X Hu 2022 41st Chinese Control Conference (CCC), 1515-1522 , 2022 2022 Citations: 11
Visual servoing of flexible manipulators with unknown camera intrinsic parameters and vibration states K Li, F Xu, H Zhang, H Wang IEEE/ASME Transactions on Mechatronics 29 (1), 510-520 , 2023 2023 Citations: 9
A convex optimization approach to inverse optimal control Y Li, H Zhang, Y Yao, X Hu 2018 37th Chinese control conference (CCC), 257-262 , 2018 2018 Citations: 9
Discrete-time inverse linear quadratic optimal control over finite time-horizon under noisy output measurements H Zhang, Y Li, X Hu Control Theory and Technology 19 (4), 563-572 , 2021 2021 Citations: 8
K-bmpc: Derivative-based koopman bilinear model predictive control for tractor-trailer trajectory tracking with unknown parameters Z Wang, H Zhang, J Wang 2024 IEEE International Conference on Robotics and Automation (ICRA), 5808-5813 , 2024 2024 Citations: 7
Error Dynamics in Affine Group Systems X Li, J Chen, H Zhang, J Wei, J Wu IEEE Transactions on Automatic Control 70 (4), 2607-2614 , 2024 2024 Citations: 6
Optimization-based trajectory planning for tractor-trailer vehicles on curvy roads: A progressively increasing sampling number method Z Wang, H Zhang, J Wang, W Chen IEEE Transactions on Intelligent Transportation Systems , 2025 2025 Citations: 3
Consistent inverse optimal control for discrete-time nonlinear stochastic systems Z Wang, H Zhang, A Ringh arXiv preprint arXiv:2511.22579 , 2025 2025 Citations: 1
A 4D Radar Camera Extrinsic Calibration Tool Based on 3D Uncertainty Perspective N Points C Cao, X Wang, W Xi, H Zhang, W Chen, J Wang 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems … , 2025 2025 Citations: 1
U-OBCA: Uncertainty-Aware Optimization-Based Collision Avoidance via Wasserstein Distributionally Robust Chance Constraints Z Wang, Y Tang, H Zhang, J Wang, W Chen arXiv preprint arXiv:2603.04914 , 2026 2026
Consistent inverse optimal control for infinite time-horizon discounted nonlinear systems under noisy observations Z Wang, A Ringh, H Zhang arXiv preprint arXiv:2602.07874 , 2026 2026
