2025

最新文章

• Analysis of Gradient Descent With Varying Step Sizes Using Integral Quadratic Constraints AI翻译
  作者：Padmanabhan, Ram; Seiler, Peter
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; University of Michigan System; University of Michigan
  摘要：The framework of integral quadratic constraints is used to perform an analysis of gradient descent with varying step sizes. Two performance metrics are considered: convergence rate and noise amplification. We assume that the step size is produced from a line search and varies in a known interval. Modeling the algorithm as a linear parameter-varying (LPV) system, we construct a parameterized linear matrix inequality condition that certifies algorithm performance, which is solved using a result ...
• Prescribed-Time Control of Disturbed Systems With State and Input Constraints AI翻译
  作者：Vazquez, Carlos Renato
  作者单位：Tecnologico de Monterrey
  摘要：Practical control applications frequently require state and input constraints. Even more, certain applications may require the controller to fit with a strict time scheduling. In this context, this article proposes a control scheme that ensures convergence to the origin in prescribed-time for both linear controllable systems and nonlinear systems in the normal form, under nonvanishing disturbances. In this, the settling time is an explicit parameter given by the designer. Moreover, a planning ...
• Optimal Parameter Selection for ADMM: Quadratically Constrained Quadratic Program AI翻译
  作者：Nguyen, Hoai-Nam
  作者单位：IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom SudParis
  摘要：We propose two new algorithms for solving quadratically constrained quadratic programming (QCQP) problems arising from real-time optimization based control such as model predictive control or interpolating control. The proposed algorithms are based on the Alternating Direction Method of Multipliers (ADMM). ADMM is a powerful tool for solving a wide class of constrained optimization problems. There are two main challenges when applying ADMM: Its performance depends greatly on the efficiency of ...
• Analysis and Stabilization of Linear Cone-Preserving Systems With Bounded Inputs AI翻译
  作者：Qiu, Hongling; Shen, Jun
  作者单位：Nanjing University of Aeronautics & Astronautics
  摘要：This article focuses on estimating the domain of attraction for linear cone-preserving systems subject to saturated linear feedback. The considered system model belongs to a category of control systems whose state trajectories are constrained within proper cones. In terms of cone max norms induced by proper cones, an extended max-separable Lyapunov function is constructed. Furthermore, sufficient criteria are given to show that the level set of this Lyapunov function is contractively invariant...
• Energy-Constrained Optimal Stealthy Attack Against State Estimation With Multichannel Protocol AI翻译
  作者：Mao, Dancheng; Niu, Yugang; Xu, Kun
  作者单位：East China University of Science & Technology
  摘要：Research on attack design provides a reference for attack defense. To this end, this work considers the design problem of an optimal energy-constrained stealthy attack strategy orienting remote estimation. The signals from smart sensors to remote estimators are scheduled via an extended Round-Robin protocol, which sends data through each channel in a specific order, and allows more than one channel to be transitable at each instant. To achieve the optimal attack strategy that can maximize the ...
• Quantifying the Satisfaction of Spatio-Temporal Logic Specifications for Multiagent Control AI翻译
  作者：Liu, Wenliang; Alsalehi, Suhail; Mehdipour, Noushin; Bartocci, Ezio; Belta, Calin
  作者单位：Boston University; Boston University; Technische Universitat Wien; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park
  摘要：In this article, we study control synthesis problems for multiagent systems (MASs) that must comply with spatio-temporal logic requirements. We define a logic called team spatio-temporal reach and escape logic (t-STREL) and a robustness metric for it that is continuous everywhere and differentiable almost everywhere. These properties facilitate the use of gradient-based optimization and learning-based control techniques, offering greater efficiency compared to traditional gradient-free methods...
• Constrained Optimization With Decision-Dependent Distributions AI翻译
  作者：Wang, Zifan; Liu, Changxin; Parisini, Thomas; Zavlanos, Michael M.; Johansson, Karl H.
  作者单位：Royal Institute of Technology; East China University of Science & Technology; Imperial College London; Aalborg University; University of Trieste; Duke University
  摘要：In this article, we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the ...
• Quantifying the Value of Preview Information for Safety Control AI翻译
  作者：Liu, Zexiang; Ozay, Necmiye
  作者单位：University of Michigan System; University of Michigan
  摘要：Safety-critical systems, such as autonomous vehicles, often incorporate perception modules that can anticipate upcoming disturbances to system dynamics, expecting that such preview information can improve the performance and safety of the system in complex and uncertain environments. However, there is a lack of formal analysis of the impact of preview information on safety. In this work, we introduce a notion of safety regret, a properly defined difference between the maximal invariant set of ...
• A General Framework for the Bearing-Based Formation Control AI翻译
  作者：Cheng, Haoshu; Huang, Jie
  作者单位：Nanyang Technological University; Chinese University of Hong Kong
  摘要：The bearing-based formation control has been an active research topic over the past decade. However, the existing results mainly focus on single- or double-integrator systems and assume that all the leaders move with a constant velocity. In this article, we aim to establish a general framework to handle the bearing-based formation control. The framework offers three features. First, our problem is formulated for general heterogeneous multiagent linear systems, which include high-order integrat...
• Sample-Efficient Reinforcement Learning With Temporal Logic Objectives: Leveraging the Task Specification to Guide Exploration AI翻译
  作者：Kantaros, Yiannis; Wang, Jun
  作者单位：Washington University (WUSTL)
  摘要：In this article, we address the problem of learning optimal control policies for systems with uncertain dynamics and high-level control objectives specified as linear temporal logic (LTL) formulas. Uncertainty is considered in the workspace structure and the outcomes of control decisions giving rise to an unknown Markov decision process (MDP). Existing reinforcement learning (RL) algorithms for LTL tasks typically rely on exploring a product MDP state-space uniformly (using e.g., an $\epsilon$...