2024

最新文章

• Relative Q-Learning for Average-Reward Markov Decision Processes With Continuous States AI翻译
  作者：Yang, Xiangyu; Hu, Jiaqiao; Hu, Jian-Qiang
  作者单位：Shandong University; State University of New York (SUNY) System; Stony Brook University; Fudan University
  摘要：Markov decision processes (MDPs) are widely used for modeling sequential decision-making problems under uncertainty. We propose an online algorithm for solving a class of average-reward MDPs with continuous state spaces in a model-free setting. The algorithm combines the classical relative Q-learning with an asynchronous averaging procedure, which permits the Q-value estimate at a state-action pair to be updated based on observations at other neighboring pairs sampled in subsequent iterations....
• Linear Quadratic Path-Following via Online Trajectory Speed Optimization AI翻译
  作者：Antunes, Duarte J.
  作者单位：Eindhoven University of Technology
  摘要：Consider a linear system subject to stochastic disturbances and a path to be followed by a system's output. The path-following problem is posed here as choosing both the control input and the speed along the path to minimize the expected value of a quadratic function of the control input and of the error between the output and the resulting trajectory. The optimal control input policy for the deterministic version (no stochastic disturbances) is first provided and shown to be the sum of linear...
• Input-Constrained Funnel Control of Nonlinear Systems AI翻译
  作者：Berger, Thomas
  作者单位：University of Paderborn
  摘要：We study tracking control for uncertain nonlinear multi-input, multi-output systems modeled by rth order functional differential equations (encompassing systems with arbitrary strict relative degree) in the presence of input constraints. The objective is to guarantee the evolution of the tracking error within a performance funnel with prescribed asymptotic shape (thus achieving desired transient and asymptotic accuracy objectives), for any sufficiently smooth reference signal. We design a nove...
• Distributed Constrained Optimization Over Unbalanced Time-Varying Digraphs: A Randomized Constraint Solving Algorithm AI翻译
  作者：Luan, Meng; Wen, Guanghui; Lv, Yuezu; Zhou, Jialing; Chen, C. L. Philip
  作者单位：Southeast University - China; Beijing Institute of Technology; South China University of Technology
  摘要：Despite the recent development of distributed constrained optimization algorithms in the literature, it is still a challenging issue to construct distributed algorithms to efficiently solve the constrained optimization problem with convergence rate guarantees, especially for the case with general constraints and unbalanced time-varying digraphs. This article aims to investigate the distributed discrete-time optimization problem over time-varying unbalanced digraphs with general constraints inc...
• Strategically Revealing Intentions in General Lotto Games AI翻译
  作者：Paarporn, Keith; Chandan, Rahul; Kovenock, Dan; Alizadeh, Mahnoosh; Marden, Jason R.
  作者单位：University of Colorado System; University of Colorado at Colorado Springs; University of California System; University of California Santa Barbara; Chapman University System; Chapman University
  摘要：Strategic decision-making in uncertain and adversarial environments is crucial for the security of modern systems and infrastructures. A salient feature of many optimal decision-making policies is a level of unpredictability, or randomness, which helps to keep an adversary uncertain about the system's defensive strategies. This article seeks to explore decision-making policies on the other end of the spectrum-namely, whether there are benefits in revealing one's strategic intentions to an oppo...
• Theoretical Relationship of Set-Based Robust State Estimators: An Optimality Perspective AI翻译
  作者：Fan, Yidian; Xu, Feng
  作者单位：Tsinghua University; Tsinghua Shenzhen International Graduate School
  摘要：This article establishes a mathematical framework for discrete-time linear time-invariant systems to compare the optimal state estimation performance of the set-membership estimator, set-valued observer, and interval observer in the polytopic representation. First, the ability of observer gains in reducing the conservatism of state estimation sets is characterized by the support function. Second, the optimal estimation results given by the set-valued and interval observers are derived rigorous...
• Singular-Perturbations-Based Analysis of Dynamic Consensus in Directed Networks of Heterogeneous Nonlinear Systems AI翻译
  作者：Maghenem, Mohamed; Panteley, Elena; Loria, Antonio
  作者单位：Communaute Universite Grenoble Alpes; Institut National Polytechnique de Grenoble; Universite Grenoble Alpes (UGA); Centre National de la Recherche Scientifique (CNRS); Centre National de la Recherche Scientifique (CNRS); Universite Paris Saclay
  摘要：We investigate conditions under which heterogeneous nonlinear systems, interconnected over a directed static network, may achieve synchrony. Due to the network's heterogeneity, complete synchronization is impossible in general, but an emergent dynamics arises. This may be characterized by two dynamical systems evolving in two timescales. The first, which is slow, corresponds to the dynamics of the network on the synchronization manifold. The second, which is fast, corresponds to that of the sy...
• Data-Driven System Analysis of Nonlinear Systems Using Polynomial Approximation AI翻译
  作者：Martin, Tim; Allgoewer, Frank
  作者单位：University of Stuttgart
  摘要：In the context of data-driven control of nonlinear systems, many approaches lack of rigorous guarantees, call for nonconvex optimization, or require knowledge of a function basis containing the system dynamics. To tackle these drawbacks, we establish a polynomial representation of nonlinear functions based on a polynomial sector by Taylor's theorem and a set-membership for Taylor polynomials. The latter is obtained from finite noisy samples. By incorporating the measurement noise, the error of...
• Low-Computational-Complexity Zeroing Neural Network Model for Solving Systems of Dynamic Nonlinear Equations AI翻译
  作者：Zheng, Kangze; Li, Shuai; Zhang, Yunong
  作者单位：Sun Yat Sen University; University of Oulu; VTT Technical Research Center Finland
  摘要：Nonlinear equation systems are ubiquitous in a variety of fields, and how to tackle them has drawn much attention, especially dynamic ones. As a particular class of recurrent neural network, the zeroing neural network (ZNN) takes time-derivative information into consideration, and thus, is a competent approach to dealing with dynamic problems. Hitherto, two kinds of ZNN models have been developed for solving systems of dynamic nonlinear equations. One of them is explicit, involving the computa...
• A Second-Order Generalization of TC and DC Kernels AI翻译
  作者：Zorzi, Mattia
  作者单位：University of Padua
  摘要：Kernel-based methods have been successfully introduced in system identification to estimate the impulse response of a linear system. Adopting the Bayesian viewpoint, the impulse response is modeled as a zero mean Gaussian process whose covariance function (kernel) is estimated from the data. The most popular kernels used in system identification are the tuned-correlated (TC), the diagonal-correlated (DC) and the stable spline (SS) kernel. TC and DC kernels admit a closed-form factorization of ...