IEEE Transactions on Automatic Control

最新文章

• Single Module Identifiability in Linear Dynamic Networks With Partial Excitation and Measurement AI翻译
  作者：Shi, Shengling; Cheng, Xiaodong; Van den Hof, Paul M. J.
  作者单位：Eindhoven University of Technology; University of Cambridge
  摘要：Identifiability of a single module in a network of transfer functions is determined by whether a particular transfer function in the network can be uniquely distinguished within a network model set, on the basis of data. Whereas previous research has focused on the situations that all network signals are either excited or measured, we develop generalized analysis results for the situation of partial measurement and partial excitation. As identifiability conditions typically require a sufficien...
• Adaptive Control of Hyperbolic PDEs Coupled With a Disturbed and Highly Uncertain ODE AI翻译
  作者：Wang, Ji; Tang, Shu-Xia; Krstic, Miroslav
  作者单位：Xiamen University; Texas Tech University System; Texas Tech University; University of California System; University of California San Diego
  摘要：In this article, we address adaptive output-feedback boundary control of coupled hyperbolic partial differential equations (PDEs) with spatially varying coefficients and on a time-varying domain, whose uncontrolled boundary is coupled with a disturbed ordinary differential equation (ODE), where multiple parameters in the state matrix and the amplitudes of the harmonic disturbance are unknown. The asymptotic convergence to zero of the ODE state and the boundedness of the PDE states are ensured....
• Closed-Loop Output Error Approaches for Drone's Physics Informed Trajectory Inference AI翻译
  作者：Perrusquia, Adolfo; Guo, Weisi
  作者单位：Cranfield University
  摘要：The design of adequate countermeasures against drone's threats needs accurate trajectory estimation to avoid economic damage to the aerospace industry and national infrastructure. As trajectory estimation algorithms need highly accurate physics informed models or offline learning algorithms, radical innovation in online trajectory inference is required. In this article, a novel drone's physics informed trajectory inference algorithm is proposed. The algorithm constructs a physic informed model...
• A General Framework to Distribute Iterative Algorithms With Localized Information Over Networks AI翻译
  作者：Timoudas, Thomas Ohlson; Zhang, Silun; Magnusson, Sindri; Fischione, Carlo
  作者单位：RISE Research Institutes of Sweden; Massachusetts Institute of Technology (MIT); Stockholm University; Royal Institute of Technology
  摘要：Emerging applications in the Internet of Things (IoT) and edge computing/learning have sparked massive renewed interest in developing distributed versions of existing (centralized) iterative algorithms often used for optimization or machine learning purposes. While existing work in the literature exhibits similarities, for the tasks of both algorithm design and theoretical analysis, there is still no unified method or framework for accomplishing these tasks. This article develops such a genera...
• Dissipativity-Based Event-Triggered Sliding Mode Control of Discrete-Time 2-D Systems AI翻译
  作者：Yang, Rongni; Zheng, Wei Xing
  作者单位：Shandong University; Western Sydney University
  摘要：This article focuses on dissipativity analysis and dissipativity-based sliding mode control (SMC) of discrete-time two-dimensional (2-D) systems described by Roesser model. First, dissipativity is introduced for 2-D systems. Aimed at the characteristics of Roesser model, the horizontal and vertical sliding surface functions are constructed for the addressed 2-D systems, respectively. Then, sufficient conditions are proposed to guarantee the asymptotic stability and the prespecified dissipativi...
• A Sampling Control Framework and Its Applications to Robust and Adaptive Control AI翻译
  作者：Zhu, Lijun; Chen, Zhiyong
  作者单位：Huazhong University of Science & Technology; Huazhong University of Science & Technology; University of Newcastle
  摘要：In this article, we propose a novel sampling control framework based on the emulation technique where the sampling error is regarded as an auxiliary input to the emulated system. Utilizing the supremum norm of sampling error, the design of periodic sampling and event-triggered control law renders the error dynamics bounded-input-bounded-state, and when it is coupled with system dynamics, achieves global or semiglobal stabilization. The proposed framework is then extended to tackle the stabiliz...
• Distributed Neighbor Selection in Multiagent Networks AI翻译
  作者：Shao, Haibin; Pan, Lulu; Mesbahi, Mehran; Xi, Yugeng; Li, Dewei
  作者单位：Shanghai Jiao Tong University; University of Washington; University of Washington Seattle
  摘要：Achieving consensus via nearest neighbor rules is an important prerequisite for multiagent networks to accomplish collective tasks. A common assumption in consensus setup is that each agent interacts with all its neighbors. This article examines whether network functionality and performance can be maintained-and even enhanced-when agents interact only with a subset of their respective (available) neighbors. As shown in this article, the answer to this inquiry is affirmative. In this direction,...
• Finite-Dimensional Characterization of Optimal Control Laws Over an Infinite Horizon for Nonlinear Systems AI翻译
  作者：Sassano, Mario; Mylvaganam, Thulasi
  作者单位：University of Rome Tor Vergata; Imperial College London
  摘要：Infinite-horizon optimal control problems for nonlinear systems are considered. Due to the nonlinear and intrinsically infinite-dimensional nature of the task, solving such optimal control problems is challenging. In this article, an exact finite-dimensional characterization of the optimal solution over the entire horizon is proposed. This is obtained via the (static) minimization of a suitably defined function of (projected) trajectories of the underlying Hamiltonian dynamics on a hypersphere...
• Advances in Discrete-State-Feedback Stabilization of Highly Nonlinear Hybrid Systems by Razumikhin Technique AI翻译
  作者：Xu, Henglei; Mao, Xuerong
  作者单位：University of Strathclyde
  摘要：In this article, the authors apply the Razumikhin technique to investigate the stabilization of hybrid stochastic systems by feedback control based on discrete-time state observations, rather than the widely used comparison idea or Lyapunov functional method to this problem. Further, we extend the Razumikhin method to study the asymptotic boundedness of hybrid stochastic systems. The coefficients of these stochastic systems considered do not meet the usual linear growth condition, but are high...
• From Generalized Gauss Bounds to Distributionally Robust Fault Detection With Unimodality Information AI翻译
  作者：Shang, Chao; Ye, Hao; Huang, Dexian; Ding, Steven X.
  作者单位：Tsinghua University; University of Duisburg Essen
  摘要：The need for exact distributions in probabilistic fault detection design is hardly fulfilled. The recent moment-based distributionally robust fault detection (DRFD) design secures robustness against inexact distributions but suffers from overpessimism. To address this issue, we develop a new DRFD design scheme by using unimodality, a ubiquitous property of real-life distributions. To evaluate worst-case false alarm rates, a new generalized Gauss bound is first attained, which is less conservat...