2025

最新文章

• Computing Optimal Joint Chance Constrained Control Policies AI翻译
  作者：Schmid, Niklas; Fochesato, Marta; Li, Sarah H. Q.; Sutter, Tobias; Lygeros, John
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Konstanz
  摘要：We consider the problem of optimally controlling stochastic, Markovian systems subject to joint chance constraints over a finite-time horizon. For such problems, standard dynamic programming is inapplicable due to the time correlation of the joint chance constraints, which calls for non-Markovian, and possibly stochastic, policies. Hence, despite the popularity of this problem, solution approaches capable of providing provably optimal and easy-to-compute policies are still missing. We fill thi...
• Distributionally Robust Kalman Filtering With Volatility Uncertainty AI翻译
  作者：Han, Bingyan
  作者单位：Hong Kong University of Science & Technology (Guangzhou)
  摘要：This work presents a distributionally robust Kalman filter to address uncertainties in noise covariance matrices and predicted covariance estimates. We adopt a distributionally robust formulation using bicausal optimal transport to characterize a set of plausible alternative models. The optimization problem is transformed into a convex nonlinear semi-definite programming problem and solved using the trust-region interior point method with the aid of $LDL<^>\top$ decomposition. The empirical ou...
• A Novel and Efficient Order Reduction for Both Constrained Convex Generators and Constrained Zonotopes AI翻译
  作者：Rego, Francisco; Silvestre, Daniel
  作者单位：Lusofona University; Universidade de Lisboa; Universidade de Coimbra
  摘要：A central challenge with any reachability technique is the growth over time of the data structures that store the set-valued estimates. There are various techniques established for constrained zonotopes (CZs), although their computational complexity represents a limiting factor on the size of the set descriptions when running the methods in real time. Thus, when running a guaranteed state observer to estimate the state of a dynamical system using CZs, the number of generators and constraints h...
• Performance-Robustness Tradeoffs in Adversarially Robust Control and Estimation AI翻译
  作者：Lee, Bruce D.; Zhang, Thomas T. C. K.; Hassani, Hamed; Matni, Nikolai
  作者单位：University of Pennsylvania
  摘要：Efforts by the reinforcement learning community to close the sim-to-real gap have resulted in policy optimization objectives, which are distinct from, although related to, existing objectives in robust control, such as H-infinity methods. The disparity from the familiar control methods makes it challenging to make rigorous claims about these methods, and to predict the implications on performance of training a policy with a particular level of robustness. This in turn makes selecting the level...
• Assessment of Multilevel Intransitive Noninterference by Nonblocking Analysis AI翻译
  作者：Zhong, Wenjing; Zhao, Jinjing; Hu, Hesuan
  作者单位：Xidian University; Nanyang Technological University; Xi'an Jiaotong University
  摘要：Security of system behavior is a kind of information flow security, which is achieved by confusing the intruders via the indistinguishability of system behaviors. Noninterference is a typical notion to describe information flow security, for which multilevel intransitive noninterference (MINI) is an advanced variant. Since there is a lack of rigorous approach to assessing MINI, this article achieves so via observability theory. For systems modeled by labeled Petri nets (LPNs), two MINI propert...
• Optimally Selected Cycle-Based ILC for System With Randomly Varying Initial State AI翻译
  作者：Gao, Kaihua; Zhou, Yuanqiang; Gao, Furong; Lu, Jingyi
  作者单位：Hong Kong University of Science & Technology; Tongji University; Hong Kong University of Science & Technology; Hong Kong University of Science & Technology; East China University of Science & Technology
  摘要：Iterative learning control (ILC) is a widely used method for controlling repetitive processes. However, its superior learning capability from cycle to cycle is mostly predicated on the assumption that the initial state for all cycles is identical and at the desired point. In engineering practice, this assumption can be overly strict. A more common scenario involves the initial state varying randomly from cycle to cycle. In this article, we propose an optimally selected cycle-based ILC scheme t...
• Event-Triggered Control for Nonlinear Uncertain Strict-Feedback Systems: An Adaptive Filtering Approach AI翻译
  作者：Shahvali, Milad; Polycarpou, Marios M.
  作者单位：University of Cyprus; University of Cyprus
  摘要：This note proposes a novel output-feedback event-triggered control method for nonlinear uncertain strict-feedback systems. It incorporates dual asynchronous triggering mechanisms for both the system's output and control input, utilizing a specifically designed adaptive filtering method. The first mechanism aims to reduce the burden on sensor to controller communication, while the second determines when the controller needs to be updated. Particularly, an adaptive neural state observer, reliant...
• State Estimation of Timed Automata Under Partial Observation AI翻译
  作者：Gao, Chao; Lefebvre, Dimitri; Seatzu, Carla; Li, Zhiwu; Giua, Alessandro
  作者单位：Xidian University; University of Cagliari; Universite Le Havre Normandie; Macau University of Science & Technology
  摘要：In this article, we consider partially observable timed automata endowed with a single clock. A time interval is associated with each transition specifying at which clock values it may occur. In addition, a resetting condition associated to a transition specifies how the clock value is updated upon its occurrence. This work deals with the estimation of the current state given a timed observation, i.e., a succession of pairs of an observable event and the time instant at which the event has occ...
• Error-Free Approximation of Explicit Linear MPC Through Lattice Piecewise Affine Expression AI翻译
  作者：Xu, Jun; Lou, Yunjiang; De Schutter, Bart; Xiong, Zhenhua
  作者单位：Harbin Institute of Technology; Delft University of Technology; Shanghai Jiao Tong University
  摘要：In this article, the disjunctive and conjunctive lattice piecewise affine (PWA) approximations of explicit linear model predictive control (MPC) are proposed. Training data consisting of states and corresponding affine control laws are generated in a control invariant set, and redundant sample points are removed to simplify the construction of lattice PWA approximations. Resampling is proposed to guarantee the equivalence of lattice PWA approximations and optimal MPC control law at the sample ...
• Robust Online Learning Over Networks AI翻译
  作者：Bastianello, Nicola; Deplano, Diego; Franceschelli, Mauro; Johansson, Karl H.
  作者单位：Royal Institute of Technology; University of Cagliari
  摘要：The recent deployment of multiagent networks has enabled the distributed solution of learning problems, where agents cooperate to train a global model without sharing their local, private data. This work specifically targets some prevalent challenges inherent to distributed learning: 1) online training, i.e., the local data change over time; 2) asynchronous agent computations; 3) unreliable and limited communications; and 4) inexact local computations. To tackle these challenges, we apply the ...