6期

最新文章

• Deep Learning of Delay-Compensated Backstepping for ReactionDiffusion PDEs AI翻译
  作者：Wang, Shanshan; Diagne, Mamadou; Krstic, Miroslav
  作者单位：University of Shanghai for Science & Technology; University of California System; University of California San Diego
  摘要：With deep neural network approximations of partial differential equation (PDE) backstepping, for each new functional coefficient of the PDE plant, the gains are obtained through a function evaluation. In this article, we expand this framework to control of cascaded PDE systems from distinct classes: a reaction-diffusion plant, which is a parabolic PDE, with input delay, which is a hyperbolic PDE. The DeepONet-approximated nonlinear operator for the control gain is a cascade/composition of the ...
• Finite-Time Stochastic Integral Input-to-State Stability Revisited and Its Further Applications AI翻译
  作者：Xie, Ruiming; Xu, Shengyuan
  作者单位：Nanjing University of Science & Technology
  摘要：In this article, we revisit finite-time stochastic integral input-to-state stability (FT-SiISS) and gives its further applications. Its contributions are two-fold: first, FT-SiISS is further discussed by reconstructing two new counterexamples that are different from Cui and Xie (2023), whose research significance is to find more practical systems satisfying FT-SiISS rather than FT-SISS. Second, as its application, we further solve the problem of finite-time stabilization for more general stoch...
• Multiagent Reinforcement Learning for Constrained Markov Decision Processes by Consensus-Based PrimalDual Method AI翻译
  作者：Cui, Gaochen; Jia, Qing-Shan; Guan, Xiaohong
  作者单位：Tsinghua University; Xi'an Jiaotong University
  摘要：In this work, we consider multiagent reinforcement learning for constrained Markov decision processes and develop a consensus-based primal-dual method to solve the problem, which is model-free and with provable convergence. Compared with existing methods, our algorithm does not require the dynamic model of the system, nor ask the agents to share their local policies. The constraint is incorporated in the objective function to form the Lagrangian with the dual variables updated through the prim...
• Data-Driven Mode Detection and Stabilization of Unknown Switched Linear Systems AI翻译
  作者：Eising, Jaap; Liu, Shenyu; Martinez, Sonia; Cortes, Jorge
  作者单位：University of California System; University of California San Diego; Swiss Federal Institutes of Technology Domain; ETH Zurich; Beijing Institute of Technology; University of California System; University of California San Diego
  摘要：This article considers the stabilization of unknown switched linear systems using data. Instead of a full system model, we have access to a finite number of trajectories of each of the different modes prior to the online operation of the system. On the basis of informative enough measurements, we design an online switched controller that alternates between a mode detection phase and a stabilization phase. Since the currently active mode is unknown, the controller employs online measurements to...
• Discrete-Time Conewise Linear Systems With Finitely Many Switches AI翻译
  作者：Daafouz, Jamal; Loheac, Jerome; Morarescu, Irinel-Constantin; Postoyan, Romain
  作者单位：Universite de Lorraine; Centre National de la Recherche Scientifique (CNRS); Institut Universitaire de France
  摘要：In this article, we investigate discrete-time conewise linear systems (CLS) for which all the solutions exhibit a finite number of switches. By switches, we mean transitions of a solution from one cone to another. Our interest in this class of CLS comes from the optimization-based control of an insulin infusion model, for which the fact that solutions switch finitely many times appears to be key to establish the global exponential stability of the origin. The stability analysis of this class o...
• Coordinated Multiagent Patrolling With State-Dependent Cost Rates: Asymptotically Optimal Policies for Large-Scale Systems AI翻译
  作者：Fu, Jing; Wang, Zengfu; Chen, Jie
  作者单位：Royal Melbourne Institute of Technology (RMIT); Northwestern Polytechnical University; Northwestern Polytechnical University; City University of Hong Kong
  摘要：We study a large-scale patrol problem with state-dependent costs and multiagent coordination. We consider heterogeneous agents, rather general reward functions, and the capabilities of tracking agents' trajectories. We model the problem as a discrete-time Markov decision process consisting of parallel stochastic processes. The problem exhibits an excessively large state space, which increases exponentially in the number of agents and the size of patrol region. By randomizing all the action var...
• PI-Based Set-Point Learning Control for Batch Processes With Unknown Dynamics and Nonrepetitive Uncertainties AI翻译
  作者：Hao, Shoulin; Liu, Tao; Rogers, Eric; Wang, Youqing; Paszke, Wojciech
  作者单位：Dalian University of Technology; Dalian University of Technology; University of Southampton; Beijing University of Chemical Technology; University of Zielona Gora
  摘要：For industrial batch processes with unknown dynamics subject to nonrepetitive initial conditions and disturbances, this article develops a novel adaptive data-driven set-point learning control (ADDSPLC) scheme based on only the measured process input and output data, which has two loops, one for the dynamics within a batch and the other for the batch-to-batch dynamics. In the former case, a model-free tuning strategy is first presented for determining the closed-loop proportional-integral cont...
• Robust String Stabilization of Connected Vehicles With Jerk Feedforward AI翻译
  作者：Ma, Guoqi; Ge, Shuzhi Sam
  作者单位：Texas A&M University System; Texas A&M University College Station; National University of Singapore
  摘要：This article investigates the effect of communicated jerk on string stabilization of connected vehicles with uncertain parasitic actuation lags. First, by feeding forward the jerk of the preceding vehicle through vehicle-to-vehicle communication, a modified cooperative adaptive cruise control law is formulated. Second, the corresponding governing equation that characterizes the propagation of the intervehicular spacing errors along the stream is deduced. Based on the resultant intervehicular s...
• Robust Dynamic Corrective Consensus Over Lossy Networks With GilbertElliott Channels AI翻译
  作者：Manfredi, Sabato
  作者单位：University of Naples Federico II
  摘要：In this article, we propose a distributed algorithm to track the average of time-varying reference signals at nodes (i.e., dynamic average consensus) over networks with heterogeneous, asymmetric Gilbert-Elliott (GE) type lossy channels. The algorithm is robust to GE type network disruptions, (re)-initialization errors and agents joining, faulty or leaving the network during time. Necessary and sufficient conditions are formulated to assess almost sure and mean bounded dynamic average consensus...
• Temporal Parallelization of the HJB Equation and Continuous-Time Linear Quadratic Control AI翻译
  作者：Sarkka, Simo; Garcia-Fernandez, Angel F.
  作者单位：Aalto University; University of Liverpool
  摘要：This article presents a mathematical formulation to perform temporal parallelization of continuous-time optimal control problems, which can be solved via the Hamilton-Jacobi-Bellman (HJB) equation. We divide the time interval of the control problem into subintervals, and define a control problem in each subinterval, conditioned on the start and end states, leading to conditional value functions for the subintervals. By defining an associative operator as the minimization of the sum of conditio...