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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Bowen Zhao Xuefei Yang Emilia Fridman Bin Zhou Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China School of Electrical Engineering Tel-Aviv University Israel

In this article, we introduce a time-delay approach to extremum seeking (ES) for scalar static quadratic maps with measurement noise. The approach involves transforming the ES system into a time-delay neutral type system with stochastic perturbations, which guarantees the stability of the original ES system. Using a Lyapunov-Krasovskii (L-K) method, explicit conditions are established for the mean-square ultimate boundedness of the ES control systems. These conditions are expressed in terms of LMIs and depend on the intensity of measurement noise, tuning parameters, and a known arbitrarily large constant $L$ that bounds the 6th moment of the estimation error. Compared to existing results for ES with measurement noise obtained via qualitative analysis, our approach provides a quantitative analysis via a time-delay approach to averaging. A numerical example is provided to illustrate the efficiency of the proposed method.

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Anomaly Detection for Stochastic Networked Cyber-Physical Systems: A Statistical Approach

Anomaly Detection for Stochastic Networked Cyber-Physical Sy...

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International Conference on control and Automation (ICCA)

作者： Yamin Yan Minyue Fu Maria M. Seron School of Electrical and Electronic Engineering Nanyang Technological University Singapore Shenzhen Key Laboratory of Control Theory and Intelligent Systems and Centre for Control Science and Technology School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Engineering The University of Newcastle Callaghan NSW Australia

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In this paper, we investigate the anomaly detection problem within stochastic networked cyber-physical systems. We introduce an anomaly detection scheme centered on estimator design employing a statistical approach. Specifically, we extend the statistical method recently developed for single systems to networked control scenarios. Additionally, we analyse the detection of several representative anomalies through this statistical approach. We then apply our anomaly detection strategy to a power network system exposed to such anomalies. Our findings demonstrate that the proposed design effectively detects these anomalies, which simpler methods relying solely on residual assessment with a threshold fail to identify.

关键词： Analytical models Automation Statistical analysis Stochastic processes Cyber-physical systems control systems Anomaly detection

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A Data-Driven Approach to System Invertibility and Input Reconstruction

A Data-Driven Approach to System Invertibility and Input Rec...

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IEEE Conference on Decision and control

作者： Vikas Kumar Mishra Andrea Iannelli Naim Bajcinca Department of Mechanical and Process Engineering RPTU Kaiserslautern Kaiserslautern Germany University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart Germany

We consider the problems of system invertibility and input reconstruction for linear time-invariant (LTI) systems using only measured data. The two problems are connected in the sense that input reconstruction is possible provided that the system is left invertible. To verify the latter property without model knowledge, we leverage behavioral systems theory and develop two data-driven algorithms: one based on input/state/output data and the other based only on input/output data. We then consider the problem of input reconstruction for both noise-free and noisy data settings. In the case of noisy data, a statistical approach is leveraged to formulate the problem as a maximum likelihood estimation (MLE) problem. The proposed approaches are finally illustrated with numerical examples that show: exact input reconstruction in the noise-free setting; and the better performance of the MLE-based approach compared to the standard least-norm solution.

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A Multimodal Fusion Model for Breast Tumor Segmentation in Ultrasound Images

A Multimodal Fusion Model for Breast Tumor Segmentation in U...

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IEEE International Symposium on Biomedical Imaging

作者： Hanlong Yin Lin Tao Yue Zhao Jing Jin Control Theory and Engineering School of Astronautics Harbin Institute of Technology Harbin China Department of Mammary Surgery The Second Affiliated Hospital of Harbin Medical University Harbin China

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Breast cancer is a leading cause of death among women worldwide. Accurate segmentation of breast tumors in Bmode ultrasound (BUS) images is crucial for early detection and diagnosis. However, this task remains challenging due to indistinct boundaries and artifacts. Existing methods using only BUS images often mistake artifacts in BUS images for tumors, posing challenges in accurately delineating tumor contours. To overcome the interference of artifacts and achieve more accurate segmentation, a multimodal method combining B-mode and elastography ultrasound images for breast tumor segmentation is proposed in this study. The proposed method utilizes BUS images and elastography as dual inputs of the network because elastography can depict the stiffness of breast tissue. The attention-separation-and-aggregation gate (ASA-Gate) module is implemented to achieve cross-modal feature fusion and extraction. Experimental results on an in-house dataset demonstrated the effectiveness of the method in reducing the interference of artifacts and improving the segmentation accuracy in BUS images.

关键词： Image segmentation Ultrasonic imaging Breast tumors Accuracy Interference Feature extraction Elastography

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HUBER LOSS-BASED PENALTY APPROACH TO PROBLEMS WITH LINEAR CONSTRAINTS∗

arXiv

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arXiv 2023年

作者： Nedić, Angelia Tatarenko, Tatiana The School of Electrical Computer and Energy Engineering Arizona State University United States Department of Control Theory and Robotics TU Darmstadt Germany

We consider an optimization problem with many linear inequalities constraints. To deal with a large number of constraints, we provide a penalty reformulation of the problem, where the penalty is a variant of the one-sided Huber loss function. We study the infeasibility properties of the solutions of penalized problems for nonconvex and convex objective functions, as the penalty parameters vary with time. Then, we propose a random incremental penalty method for solving convex problem, and investigate its convergence properties for convex and strongly convex objective functions. We show that the iterates of the method converge to a solution of the original problem almost surely and in expectation for suitable choices of the penalty parameters and the stepsize. Also, we establish convergence rate of the method for appropriately defined weighted averages of the iterates for the expected function values. We establish O(ln1/2+ǫ k/√k)-convergence rate when the objective function is convex, and O(lnǫ k/k)-convergence rate when the objective function is strongly convex with ǫ being any small positive number. To the best of our knowledge, these are the first results on the convergence rate for the penalty-based incremental subgradient method with time-varying penalty parameters. © 2023, CC BY.

关键词： Iterative methods

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Distributed-Observer-Based on Longitudinal Flight control for Hypersonic Vehicle

Distributed-Observer-Based on Longitudinal Flight Control fo...

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Chinese control Conference (CCC)

作者： Yuehui Ji Yiming Zhao Jiaqi Chen Junjie Liu Qiang Gao Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

An output feedback control is investigated to achieve stable tracking of velocity and altitude in hypersonic flight vehicle in the paper. A distributed observer is proposed to estimate the unmeasurable flight path angel and angle of attack through a strongly connected directed network topology. Then, a nonlinear control is addressed on the longitudinal dynamics of a rigid hypersonic flight vehicle (HFV) with partial measurable states and the estimated states. The system dynamic is divided into the altitude subsystem and the velocity subsystem. In the altitude subsystem, the backstepping design is proposed for constructing the controllers utilizing the estimated states. The nonlinear dynamic inversion controller is introduced to accomplish the velocity tracking. Finally, numerical simulations verify the effectiveness of the proposed control scheme in providing favorable tracking performance and exact state estimation ability.

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Extremum seeking in the presence of large delays via time-delay approach to averaging

arXiv

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arXiv 2023年

作者： Yang, Xuefei Fridman, Emilia Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China School of Electrical Engineering Tel-Aviv University Israel

In this paper, we study gradient-based classical extremum seeking (ES) for uncertain n-dimensional (nD) static quadratic maps in the presence of known large constant distinct input delays and large output constant delay with a small time-varying uncertainty. This uncertainty may appear due to network-based measurements. We present a quantitative analysis via a time-delay approach to averaging. We assume that the Hessian has a nominal known part and norm-bounded uncertainty, the extremum point belongs to a known box, whereas the extremum value to a known interval. By using the orthogonal transformation, we first transform the original static quadratic map into a new one with the Hessian containing a nominal diagonal part. We apply further a time-delay transformation to the resulting ES system and arrive at a time-delay system, which is a perturbation of a linear time-delay system with constant coefficients. Given large delays, we choose appropriate gains to guarantee stability of this linear system. To find a lower bound on the dither frequency for practical stability, we employ variation of constants formula and exploit the delay-dependent positivity of the fundamental solutions of the linear system with their tight exponential bounds. Sampled-data ES in the presence of large distinct input delays is also presented. Explicit conditions in terms of simple scalar inequalities depending on tuning parameters and delay bounds are established to guarantee the practical stability of the ES control systems. We show that given any large delays and initial box, by choosing appropriate gains we can achieve practical stability for fast enough dithers and small enough uncertainties. Copyright © 2023, The Authors. All rights reserved.

关键词： Time delay

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Differentiable Constrained Imitation Learning for Robot Motion Planning and control

arXiv

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arXiv 2022年

作者： Diehl, Christopher Adamek, Janis Krüger, Martin Hoffmann, Frank Bertram, Torsten Institute of Control Theory and Systems Engineering TU Dortmund University D-44227 Germany

Motion planning and control are crucial components of robotics applications. Here, spatio-temporal hard constraints like system dynamics and safety boundaries (e.g., obstacles in automated driving) restrict the robot’s motions. Direct methods from optimal control solve a constrained optimization problem. However, in many applications finding a proper cost function is inherently difficult because of the weighting of partially conflicting objectives. On the other hand, Imitation Learning (IL) methods such as Behavior Cloning (BC) provide a intuitive framework for learning decision-making from offline demonstrations and constitute a promising avenue for planning and control in complex robot applications. Prior work primarily relied on soft-constraint approaches, which use additional auxiliary loss terms describing the constraints. However, catastrophic safety-critical failures might occur in out-of-distribution (OOD) scenarios. This work integrates the flexibility of IL with hard constraint handling in optimal control. Our approach constitutes a general framework for constraint robotic motion planning and control using offline IL. Hard constraints are integrated into the learning problem in a differentiable manner, via explicit completion and gradient-based correction. Simulated experiments of mobile robot navigation and automated driving provide evidence for the performance of the proposed method. Copyright © 2022, The Authors. All rights reserved.

关键词： Robot applications

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Distributed interval estimation for continuous-time linear systems: A two-step method ⋆

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IFAC-PapersOnLine 2023年第2期56卷 8500-8505页

作者： Zhenhua Wang Jiahui Zhang Zonglin Liu Weixin Han Mouquan Shen School of Astronautics Harbin Institute of Technology Harbin 150001 China Control and System Theory EECS University of Kassel Kassel Germany Northwestern Polytechnical University Xian P. R. China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China

This paper proposes a two-step distributed interval estimation method for continuous-time linear time-invariant (LTI) systems subject to unknown but bounded disturbance and measurement noise. First, a network of local observers is designed to obtain point-wise estimation. Second, interval estimation is obtained based on the point-wise estimation and peak-to-peak analysis. The conditions of the observer design and the peak-to-peak analysis are formulated as linear matrix inequalities, which can be solved efficiently. Compared with the distributed interval observers designed using the monotone system theory, the proposed method has less restrictive design conditions and hence broader application scopes. Moreover, the parameter matrices in the proposed method can be optimized to obtain tight interval estimation. A numerical simulation is given to illustrate the performance of the proposed method.

关键词： Continuous time linear system distributed observers interval estimation

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Displacement-Based Formation control with Measurement Noises

Displacement-Based Formation Control with Measurement Noises

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IEEE Conference on Decision and control

作者： Weiqiang Chen Liangming Chen Jie Mei Hongwei Zhang School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China Shenzhen Key Laboratory of Control Theory and Intelligent Systems Center for Control Science and Technology Southern University of Science and Technology Shenzhen China

Multi-agent formations have many practical applications. Measurement noises are inevitable in multi-agent formations, in which, however, the existing results mainly focus on special types of noises, and the analytical discussion on the effect of general noises is challenging and remains open. This motivates us to study the effect of stochastic measurement noises on displacement-based multi-agent formations, which are described by a general form of stochastic processes with finite second-order moments. First, for the case of unbiased measurement noises, a sufficient and necessary condition is derived for the existence of solutions in the stochastic dynamics of multi-agent formations. Then, several statistical features and convergence of formation errors are analyzed. In particular, for the case of unbiased measurement noises described by zero-mean wide-sense stationary processes, an upper bound on the mean square convergence of formation errors is obtained. Finally, we demonstrate the effectiveness of our theoretical results through a simulation example.

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