3期

最新文章

• Optimizing Sets of Solutions for Controlling Constrained Nonlinear Systems AI翻译
  作者：Schuermann, Bastian; Althoff, Matthias
  作者单位：Technical University of Munich
  摘要：In this article, we present a novel control approach for formally solving reach-avoid problems for constrained and disturbed nonlinear systems by optimizing over reachable sets. Reach-avoid problems arise in many modern control applications of safety-critical systems, such as autonomous driving and human-robot collaboration. They require us to control all states from a set of initial states in finite time into a final set while guaranteeing the satisfaction of state and input constraints despi...
• Robustness for Stability and Stabilization of Boolean Networks With Stochastic Function Perturbations AI翻译
  作者：Li, Haitao; Yang, Xinrong; Wang, Shuling
  作者单位：Shandong Normal University
  摘要：In genetic regulatory networks (GRNs), gene mutations often occur in a stochastic manner. As an important model of GRNs, gene mutations of Boolean networks are always described as function perturbations. This article studies the robust stability and stabilization of Boolean networks with stochastic function perturbations. A kind of parameterized set is constructed, and it is revealed that under the stochastic function perturbations, the property of finite-time stability remains unchanged when ...
• Distributed Proximal Algorithms for Multiagent Optimization With Coupled Inequality Constraints AI翻译
  作者：Li, Xiuxian; Feng, Gang; Xie, Lihua
  作者单位：City University of Hong Kong; Nanyang Technological University
  摘要：This article aims to address distributed optimization problems over directed and time-varying networks, where the global objective function consists of a sum of locally accessible convex objective functions subject to a feasible set constraint and coupled inequality constraints whose information is only partially accessible to each agent. For this problem, a distributed proximal-based algorithm, called distributed proximal primal-dual algorithm, is proposed based on the celebrated centralized ...
• Predefined-Time Output Stabilization With Second Order Sliding Mode Generation AI翻译
  作者：Ferrara, Antonella; Incremona, Gian Paolo
  作者单位：University of Pavia; Polytechnic University of Milan
  摘要：In this article, a novel second order sliding mode control strategy is proposed for relative-degree-2 nonlinear uncertain single- input-single-output (SISO) systems. To design the strategy, the phase portrait of the second order system in normal form associated with the formulated sliding mode control problem is studied. A sliding surface switching between arcs of parabolas is conceived to ensure the convergence in a predefined-time to the desired second order sliding mode. Lyapunov-based anal...
• Latency-Reliability Tradeoffs for State Estimation AI翻译
  作者：Gatsis, Konstantinos; Hassani, Hamed; Pappas, George J.
  作者单位：University of Oxford; University of Pennsylvania
  摘要：The emerging interest in low-latency high-reliability applications, such as connected vehicles, necessitates a new abstraction between communication and control. Thanks to advances in cyber-physical systems over the past decades, we understand this interface for classical bit-rate models of channels as well as packet-loss-type channels. This article proposes a new abstraction characterized as a tradeoff curve between latency, reliability, and rate. Our aim is to understand-do we (control engin...
• Stochastic Approximation for Risk-Aware Markov Decision Processes AI翻译
  作者：Huang, Wenjie; Haskell, William B.
  作者单位：Shenzhen Research Institute of Big Data; The Chinese University of Hong Kong, Shenzhen; The Chinese University of Hong Kong, Shenzhen; Purdue University System; Purdue University
  摘要：We develop a stochastic approximation-type algorithm to solve finite state/action, infinite-horizon, risk-aware Markov decision processes. Our algorithm has two loops. The inner loop computes the risk by solving a stochastic saddle-point problem. The outer loop performs Q-learning to compute an optimal risk-aware policy. Several widely investigated risk measures (e.g., conditional value-at-risk, optimized certainty equivalent, and absolute semideviation) are covered by our algorithm. Almost su...
• Over- and Under-Approximations of Reachable Sets With Series Representations of Evolution Functions AI翻译
  作者：She, Zhikun; Li, Meilun
  作者单位：Beihang University; Beihang University
  摘要：In this article, we investigate both over- and under-approximations of reachable sets for analytic autonomous dynamical systems beyond polynomial dynamics. We start with the concept of evolution function, whose subzero-level set can be used to describe reachable set, and find a series representation of the evolution function with its Lie derivatives. Afterwards, based on the partial sums of this series, two different methodologies are introduced to compute over- and under-approximations of rea...
• Dynamic Self-Triggered Controller Codesign for Markov Jump Systems AI翻译
  作者：Wan, Haiying; Luan, Xiaoli; Karimi, Hamid Reza; Liu, Fei
  作者单位：Jiangnan University; Polytechnic University of Milan
  摘要：This article proposes a resource-aware triggering-based dynamic controller codesign scheme for Markov jump systems (MJSs) to fulfill both disturbance rejection and computational resources saving goals. Specifically, a self-trigger strategy is presented for precomputing the next execution time for state measurement, executing the controller, and updating the actuators using the current sampled information. To achieve a desired system performance and reduce the resource occupation, the self-trig...
• Distributed Constrained Optimization Over Unbalanced Directed Networks Using Asynchronous Broadcast-Based Algorithm AI翻译
  作者：Li, Huaqing; Lu, Qingguo; Chen, Guo; Huang, Tingwen; Dong, Zhaoyang
  作者单位：Southwest University - China; University of New South Wales Sydney; Qatar Foundation (QF); Texas A&M University Qatar
  摘要：This article focuses on distributed convex optimization problems over an unbalanced directed multiagent (no central coordinator) network with inequality constraints. The goal is to cooperatively minimize the sum of all locally known convex cost functions. Every single agent in the network only knows its local objective function and local inequality constraint, and is constrained to a privately known convex set. Furthermore, we particularly discuss the scenario in which the interactions among a...
• Robustly Complete Synthesis of Memoryless Controllers for Nonlinear Systems With Reach-and-Stay Specifications AI翻译
  作者：Li, Yinan; Liu, Jun
  作者单位：University of Waterloo
  摘要：This article proposes a finitely terminating algorithm to solve reach-and-stay control problems for nonlinear systems. The algorithm is guaranteed to return a control strategy if the specification is robustly realizable. Such a feature is desirable as the commonly used abstraction-based methods are sound but not complete for systems that are not incrementally stable. Fundamental to the proposed method is a fixed-point characterization of the winning set of the system with respect to a given sp...