2024

最新文章

• Sublevel Set Approximation in the Hausdorff and Volume Metric With Application to Path Planning and Obstacle Avoidance AI翻译
  作者：Jones, Morgan
  作者单位：University of Sheffield
  摘要：what circumstances does the closeness of two functions imply the closeness of their respective sublevel sets? In this article, we answer this question by showing that if a sequence of functions converges strictly from above/below to a function, V , in the L-infinity (or L-1) norm then these functions yield a sequence sublevel sets that converge to the sublevel set of V with respect to the Hausdorff metric (or volume metric). Based on these theoretical results we propose sum-of-squares numerica...
• Attacks on Perception-Based Control Systems: Modeling and Fundamental Limits AI翻译
  作者：Khazraei, Amir; Pfister, Henry D.; Pajic, Miroslav
  作者单位：Duke University
  摘要：We study the performance of perception-based control systems in the presence of attacks and provide methods for modeling and analysis of their resiliency to stealthy attacks on both physical and perception-based sensing. Specifically, we consider a general setup with a nonlinear affine physical plant controlled with a perception-based controller that maps both the physical [e.g., inertial measurement units (IMUs)] and perceptual (e.g., camera) sensing to the control input; the system is also e...
• Adaptive Robust Tracking Control With Active Learning for Linear Systems With Ellipsoidal Bounded Uncertainties AI翻译
  作者：Ma, Xuehui; Zhang, Shiliang; Li, Yushuai; Qian, Fucai; Sun, Zhiyong; Huang, Tingwen
  作者单位：Xi'an University of Technology; University of Oslo; Aalborg University; Eindhoven University of Technology; Shenzhen University of Advanced Technology
  摘要：This article is concerned with the robust tracking control of linear uncertain systems, whose unknown system parameters and disturbances are bounded within ellipsoidal sets. We propose an adaptive robust control that can actively learn the ellipsoid sets. Particularly, our approach utilizes the ellipsoidal set-membership estimation in learning the ellipsoid sets, aiming at narrowing the uncertainty boundaries to reduce the conservativeness in robust control. To further improve the transient pe...
• Value Approximator-Based Learning Model Predictive Control for Iterative Tasks AI翻译
  作者：Bao, HanQiu; Kang, Qi; Shi, XuDong; Zhou, MengChu; An, Jing; Al-Turki, Yusuf
  作者单位：Tongji University; Tongji University; Zhejiang Gongshang University; Shanghai Institute of Technology; King Abdulaziz University; King Abdulaziz University
  摘要：Maximizing the performance of a system without reference over an infinite horizon is a challenging problem for iterative control tasks. This article introduces a value approximator-based learning model predictive control framework that aims to enhance the system's performance by learning from previous trajectories. We introduce a value approximator to recursively reconstruct a terminal cost function and reformulate an infinite time optimization problem to a finite time one. This work proposes ...
• Output Tracking and Regulation of Networked Control Systems Under Finite Bandwidth Constraints and Its Applications AI翻译
  作者：Jiang, Xiaowei; Li, Jianhao; Li, Bo; Wang, Yan-Wu; Huang, Tingwen
  作者单位：China University of Geosciences; Anhui University of Finance & Economics; Huazhong University of Science & Technology; Qatar Foundation (QF); Texas A&M University Qatar
  摘要：Studying the performance limitations of communication-constrained networked control systems (NCSs) is of utmost significance and poses a considerable challenge from an academic standpoint. This article investigates the tracking performance limitations (TPL) and regulation performance limitations (RPL) of a NCS with communication constraints in the network channel, such as network-induced delay, packet loss, additive non-zero mean noise, finite bandwidth, and encoding-decoding constraints. Expl...
• Finite-Time Stability Properties of Lur'e Systems With Piecewise Continuous Nonlinearities AI翻译
  作者：Mariano, S.; Postoyan, R.; Zaccarian, L.
  作者单位：University of Melbourne; Centre National de la Recherche Scientifique (CNRS); Universite de Lorraine; Universite de Toulouse; Centre National de la Recherche Scientifique (CNRS); University of Trento
  摘要：We analyze the stability properties of Lur'e systems with piecewise continuous nonlinearities by exploiting the notion of set-valued Lie derivative for Lur'e-Postnikov Lyapunov functions. We first extend an existing result of the literature to establish the global asymptotic stability of the origin under a more general sector condition. We then present the main results of this work, namely, additional conditions under which output and state finite-time stability properties also hold for the co...
• An Operator Splitting Scheme for Distributed Optimal Load-Side Frequency Control With Nonsmooth Cost Functions AI翻译
  作者：Wang, Yifan; Liu, Shuai; Cao, Xianghui; Chow, Mo-Yuen
  作者单位：Southeast University - China; Shandong University; Shanghai Jiao Tong University
  摘要：The increasing penetration of renewable energy resources and utilization of energy storage systems pose new challenges in maintaining power system's stability. Specifically, the cost function of regulation no longer remains smooth, which complicates the task of ensuring nominal frequency and power balance, particularly in a distributed manner. This article proposes a distributed proximal primal-dual (DPPD) algorithm, based on a modified primal-dual dynamics equipped with operator splitting tec...
• Neural Operators for Bypassing Gain and Control Computations in PDE Backstepping AI翻译
  作者：Bhan, Luke; Shi, Yuanyuan; Krstic, Miroslav
  作者单位：University of California System; University of California San Diego
  摘要：We introduce a framework for eliminating the computation of controller gain functions in partial differential equation (PDE) control. We learn the nonlinear operator from the plant parameters to the control gains with a (deep) neural network. We provide closed-loop stability guarantees (global exponential) under an neural network (NN)-approximation of the feedback gains. While, in the existing PDE backstepping, finding the gain kernel requires (one offline) solution to an integral equation, th...
• Provably Stable Learning Control of Linear Dynamics With Multiplicative Noise AI翻译
  作者：Coppens, Peter; Patrinos, Panagiotis
  作者单位：KU Leuven
  摘要：Control of linear dynamics with multiplicative noise naturally introduces robustness against dynamical uncertainty. Moreover, many physical systems are subject to multiplicative disturbances. In this work, we show how these dynamics can be identified from state trajectories. The least-squares scheme enables the exploitation of prior information and comes with practical data-driven confidence bounds and sample complexity guarantees. We complement this scheme with an associated control synthesis...
• Adaptive Safety with a RISE-Based Disturbance Observer AI翻译
  作者：Isaly, Axton; Patil, Omkar Sudhir; Sweatland, Hannah M.; Sanfelice, Ricardo G.; Dixon, Warren E.
  作者单位：State University System of Florida; University of Florida; University of California System; University of California Santa Cruz
  摘要：Ensuring the safety (formally, forward invariance) of control systems using control barrier functions typically requires being overly conservative when the dynamics of the control system are uncertain. In this work, we develop a disturbance observer based on the robust integral of the sign of the error (RISE) control paradigm that exponentially identifies the unknown dynamics when certain gain conditions are satisfied. The estimate of the dynamics is used in an optimization-based control law t...