9期

最新文章

• Adaptive Kalman Filtering Based on Model Parameter Ratios AI翻译
  作者：Ge, Quanbo; Li, Yunyu; Wang, Yuanliang; Hu, Xiaoming; Li, Hong; Sun, Changyin
  作者单位：Nanjing University of Information Science & Technology; Hangzhou Dianzi University; Shanghai Maritime University; Royal Institute of Technology; Southeast University - China
  摘要：This article studies an adaptive Kalman filter method based on model parameter ratio. The model parameter ratio theory is proposed for the first time, and the adaptive estimation problem is transformed into a constrained optimization problem. Compared with the existing Sage-Husa adaptive filtering algorithm, it can be seen that the application of this theory can more accurately estimate the process noise covariance and measurement noise covariance matrix, so that the algorithm has better filte...
• Incremental Versus Differential Approaches to Exponential Stability and Passivity AI翻译
  作者：Kawano, Yu; Besselink, Bart
  作者单位：Hiroshima University; University of Groningen
  摘要：There are two main Lyapunov approaches to incremental stability analysis. One is to use incremental Lyapunov functions directly, and the other is based on so-called Finsler-Lyapunov functions via contraction analysis. A system is incrementally exponentially stable if it admits either an incremental or Finsler-Lyapunov function, and the converse is also true when the Jacobian of the drift vector field satisfies a boundedness assumption. However, the direct relation between these Lyapunov functi...
• Solutions for Multiple-Defender Single-Attacker Convex Target Guarding Games: Verification via Parametric Optimization AI翻译
  作者：Lee, Yoonjae; Bakolas, Efstathios
  作者单位：University of Texas System; University of Texas Austin
  摘要：A zero-sum differential game is considered in which a team of defenders is tasked with cooperatively capturing a single attacker who seeks to breach a convex region (or target). We show that the equilibrium strategies of the agents can be computed via a convex program, which remains tractable even in high-dimensional cases as opposed to the direct solution of the Hamilton-Jacobi-Isaacs (HJI) equation. To that end, we mainly attempt to prove the validity of a candidate for the value of the game...
• Open-Loop H2/H∞ Control for Discrete-Time Mean-Field Stochastic Systems AI翻译
  作者：Ma, Hongji; Mou, Chenchen; Ho, Daniel W. C.
  作者单位：Shandong University of Science & Technology; City University of Hong Kong
  摘要：This article is concerned with the finite-horizon H-2/H-infinity control problem about discrete-time mean-field linear stochastic systems with (x, u, v) -multiplicative noises. We first present a mean-field stochastic bounded real lemma (MF-SBRL), which gives a necessary and sufficient condition for the linear perturbation operator of mean-field systems to gain an H-infinity norm less than a prescribed disturbance attenuation level. Through a mean-field forward-backward stochastic difference e...
• Revisiting the Normal Form of Input-Output Linearization AI翻译
  作者：Maggiore, Manfredi
  作者单位：University of Toronto
  摘要：This article revisits the normal form arising in the context of input-output feedback linearization for nonlinear control systems possessing well-defined relative degree. The objective is to investigate the validity of the normal form in a neighborhood of the zero dynamics manifold, as opposed to a neighborhood of a point on the manifold. The two main results of the article are necessary and sufficient conditions under which the normal form exists in some neighborhood of the zero dynamics mani...
• Estimation and Prevention of Actuator Enablement Attacks in Discrete-Event Systems Under Supervisory Control AI翻译
  作者：He, Zhaoyang; Wu, Naiqi; Li, Zhiwu
  作者单位：Macau University of Science & Technology; Xidian University
  摘要：This article addresses the problems of estimation and prevention of actuator attacks in the framework of discrete-event systems under supervisory control, where an attack estimation helps an intruder evaluate whether a controlled system can be driven to an undesirable state after being attacked based on partial observation before an actual attack is enforced. The intruder implements an actuator enablement attack by enabling a vulnerable actuator event that has been disabled by a supervisor. To...
• Boosting One-Point Derivative-Free Online Optimization via Residual Feedback AI翻译
  作者：Zhang, Yan; Zhou, Yi; Ji, Kaiyi; Shen, Yi; Zavlanos, Michael M.
  作者单位：Duke University; Utah System of Higher Education; University of Utah; University System of Ohio; Ohio State University
  摘要：Zeroth-order optimization (ZO) typically relies on two-point feedback to estimate the gradient of the objective function. Nevertheless, two-point feedback cannot be used for online optimization with time-varying objective functions, where only a single query of the function value is possible at each time step. In this work, we propose a new one-point feedback method for online optimization that estimates the gradient using the residual between two feedback points at consecutive time instants. ...
• A Distributed Bayesian Data Fusion Algorithm With Uniform Consistency AI翻译
  作者：Li, Yingke; Zhou, Enlu; Zhang, Fumin
  作者单位：University System of Georgia; Georgia Institute of Technology; University System of Georgia; Georgia Institute of Technology
  摘要：Distributed data fusion methods, which possess guaranteed performance for ad hoc and arbitrarily connected networks, empower more scalable, flexible, and robust information fusion for multirobot sensor networks. This article proposes a novel distributed Bayesian data fusion algorithm, which ensures uniform consistency, i.e., all the locally estimated distributions converge to the true distribution, for arbitrary periodically connected communication graphs. Conservative fusion via the weighted ...
• Differentially Private Distributed Stochastic Optimization with Time-Varying Sample Sizes AI翻译
  作者：Wang, Jimin; Zhang, Ji-Feng
  作者单位：University of Science & Technology Beijing; University of Science & Technology Beijing; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS
  摘要：Differentially private distributed stochastic optimization has become a hot topic due to the need for privacy protection in distributed stochastic optimization. In this article, two-time scale stochastic approximation-type algorithms for differentially private distributed stochastic optimization with time-varying sample sizes are proposed using gradient- and output-perturbation methods. For both gradient- and output-perturbation cases, the convergence of the algorithm and differential privacy ...
• Linear and Nonlinear Event-Triggered Extended State Observers for Uncertain Random Systems AI翻译
  作者：Wu, Ze-Hao; Deng, Feiqi; Zhou, Hua-Cheng; Zhao, Zhi-Liang
  作者单位：Foshan University; South China University of Technology; Central South University; North University of China
  摘要：In this article, linear and nonlinear event-triggered extended state observers are designed for a class of uncertain random systems driven by bounded noise and colored noise. Two event generators, with an ensured positive minimum interevent time for every sample path solution of the random systems, are proposed for the designs of linear and nonlinear event-triggered extended state observers, respectively. The mean square and almost sure convergence of the estimation errors of unmeasured state ...