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最新文章

• Time-Consistency in the Mean-Variance Problem: A New Perspective AI翻译
  作者：Bauerle, Nicole; Jaskiewicz, Anna
  作者单位：Helmholtz Association; Karlsruhe Institute of Technology; Wroclaw University of Science & Technology
  摘要：We investigate discrete-time mean-variance portfolio selection problems viewed as a Markov decision process. We transform the problems into a new model with a deterministic transition function for which the optimality equation holds. In this way, we can solve the problem recursively and obtain a time-consistent solution, which is an optimal solution that meets the Bellman optimality principle. We apply our technique for solving explicitly a more general framework.
• Robust Sliding Mode Boundary Stabilization for Uncertain Delay Reaction-Diffusion Systems AI翻译
  作者：Zhou, Wei-Jie; Wu, Kai-Ning; Niu, Yu-Gang
  作者单位：Harbin Institute of Technology; East China University of Science and Technology
  摘要：The robust exponential stabilization is addressed for uncertain delay reaction-diffusion systems via sliding mode boundary control (SMBC). First, a novel integral sliding mode surface (SMS) is proposed, on which system states slide to the equilibrium with an exponential convergence rate. Furthermore, the sliding mode boundary controller (SMBCr) is designed to steer system states to the SMS in finite time. A criterion is established for robust exponential stability by utilizing the Lyapunov-Kra...
• Continuous Approximations of Projected Dynamical Systems via Control Barrier Functions AI翻译
  作者：Delimpaltadakis, Giannis; Cortes, Jorge; Heemels, W. P. M. H.
  作者单位：Eindhoven University of Technology; University of California System; University of California San Diego
  摘要：Projected dynamical systems (PDSs) form a class of discontinuous constrained dynamical systems, and have been used widely to solve optimization problems and variational inequalities. Recently, they have also gained significant attention for control purposes, such as high-performance integrators, saturated control, and feedback optimization. In this work, we establish that locally Lipschitz continuous dynamics, involving Control Barrier Functions (CBFs), namely, CBF-based dynamics, approximate ...
• 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 ...
• Approximate Information States for Worst Case Control and Learning in Uncertain Systems AI翻译
  作者：Dave, Aditya; Nishanth Venkatesh, S.; Malikopoulos, Andreas A.
  作者单位：Cornell University
  摘要：In this article, we investigate discrete-time decision-making problems in uncertain systems with partially observed states. We consider a nonstochastic model, where uncontrolled disturbances acting on the system take values in bounded sets with unknown distributions. We present a general framework for decision-making in such problems by using the notion of the information state and approximate information state and introduce conditions to identify an uncertain variable that can be used to comp...
• Non-Euclidean Contraction Analysis of Continuous-Time Neural Networks AI翻译
  作者：Davydov, Alexander; Proskurnikov, Anton V.; Bullo, Francesco
  作者单位：University of California System; University of California Santa Barbara; University of California System; University of California Santa Barbara; Polytechnic University of Turin
  摘要：Critical questions in dynamical neuroscience and machine learning are related to the study of continuous-time neural networks and their stability, robustness, and computational efficiency. These properties can be simultaneously established via a contraction analysis. This article develops a comprehensive non-Euclidean contraction theory for continuous-time neural networks. Specifically, we provide novel sufficient conditions for the contractivity of general classes of continuous-time neural ne...
• Verification of State-Based Timed Opacity for Constant-Time Labeled Automata AI翻译
  作者：Li, Jun; Lefebvre, Dimitri; Hadjicostis, Christoforos N.; Li, Zhiwu
  作者单位：Xidian University; Universite Le Havre Normandie; University of Cyprus; Macau University of Science and Technology
  摘要：This article proposes and verifies two types of state-based timed opacity notions for constant-time labeled automata (a class of timed models with partially observable transitions), called [T-l,T-u]-opacity and [T-l,+infinity)-opacity . A system is said to be [T-l,T-u]-opaque (respectively, [T-l,+infinity)-opaque ) if no timed observation can lead to the exposure of specified states (called secret states ) within a finite time window (respectively, an infinite time window) starting at the time...
• Online Feedback Equilibrium Seeking AI翻译
  作者：Belgioioso, Giuseppe; Liao-McPherson, Dominic; de Badyn, Mathias Hudoba; Bolognani, Saverio; Smith, Roy S.; Lygeros, John; Dorfler, Florian
  作者单位：Royal Institute of Technology; University of British Columbia; University of Oslo
  摘要：This article proposes a unifying design framework for dynamic feedback controllers that track solution trajectories of time-varying generalized equations, such as local minimizers of nonlinear programs or competitive equilibria (e.g., Nash) of noncooperative games. Inspired by the feedback optimization paradigm, the core idea of the proposed approach is to repurpose classic iterative algorithms for solving generalized equations (e.g., Josephy-Newton, forward-backward splitting) as dynamic feed...
• Consensus-Based Thompson Sampling for Stochastic Multiarmed Bandits AI翻译
  作者：Hayashi, Naoki
  作者单位：University of Osaka
  摘要：This article considers a distributed Thompson sampling algorithm for a cooperative multiplayer multiarmed bandit problem. We consider a multiagent system in which each agent pulls an arm according to consensus-based Bayesian inference with probability matching. To estimate the reward probability of each arm, a group of agents shares the observed rewards with neighboring agents in a communication graph. Following the information exchange, each agent updates the estimation of the posterior distr...