6期

最新文章

• Online Distributed Optimization With Nonconvex Objective Functions: Sublinearity of First-Order Optimality Condition-Based Regret AI翻译
  作者：Lu, Kaihong; Wang, Long
  作者单位：Jiangsu University; Peking University
  摘要：In this article, the problem of online distributed optimization with a set constraint is solved by employing a network of agents. Each agent only has access to a local objective function and set constraint, and can only communicate with its neighbors via a digraph, which is not necessarily balanced. Moreover, agents do not have prior knowledge of their future objective functions. Different from existing works on online distributed optimization, we consider the scenario, where objective functio...
• Distributed Augmented Lagrangian Method for Link-Based Resource Sharing Problems of Multiagent Systems AI翻译
  作者：Ananduta, Wicak; Nedic, Angelia; Ocampo-Martinez, Carlos
  作者单位：Delft University of Technology; Arizona State University; Arizona State University-Tempe; Universitat Politecnica de Catalunya; Consejo Superior de Investigaciones Cientificas (CSIC); CSIC - Institut de Robotica i Informatica Industrial (IRII)
  摘要：A multiagent optimization problem motivated by the management of energy systems is discussed. The associated cost function is separable and convex although not necessarily strongly convex and there exist edge-based coupling equality constraints. In this regard, we propose a distributed algorithm based on solving the dual of the augmented problem. Furthermore, we consider that the communication network might be time-varying and the algorithm might be carried out asynchronously. The time-varying...
• Comments on Tracking Performance Guarantees in the Presence of Quantization for Uncertain Nonlinear Systems AI翻译
  作者：Huang, Xiucai; Song, Yongduan
  作者单位：Chongqing University
  摘要：In this article, we first show that the main results claimed in the paper by Bikas and Rovithakis (2021) involve some errors as the selection conditions for the design parameters are not sufficient to ensure the boundedness of all the closed-loop signals, then we provide the corresponding corrections under the same controller, so that the underlying quantized control problem can be tackled.
• An Optimal Computing Budget Allocation Tree Policy for Monte Carlo Tree Search AI翻译
  作者：Li, Yunchuan; Fu, Michael C.; Xu, Jie
  作者单位：University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park; George Mason University
  摘要：We analyze a tree search problem with an underlying Markov decision process, in which the goal is to identify the best action at the root that achieves the highest cumulative reward. We present a new tree policy that optimally allocates a limited computing budget to maximize a lower bound on the probability of correctly selecting the best action at each node. Compared to widely used upper confidence bound (UCB) tree policies, the new tree policy presents a more balanced approach to manage the ...
• Stabilization of Sampled-Data Systems With Noisy Sampling Intervals and Packet Dropouts via a Discrete-Time Approach AI翻译
  作者：Hu, Zhipei; Ren, Hongru; Deng, Feiqi; Li, Hongyi
  作者单位：Shantou University; Shantou University; Guangdong University of Technology; Guangdong University of Technology; South China University of Technology
  摘要：In real-world applications, sampled-data systems are often subject to undesirable physical constraints, which results in noisy sampling intervals that fluctuate around an ideal sampling period based on certain probability distribution. In the presence of noisy sampling intervals, this article is concerned with the stabilization problem for a class of sampled-data systems with successive packet dropouts. First, the relationship between two adjacent update times of zero-order hold is established...
• LMI Framework for Set Reachability Inclusion in Discrete-Time LTI Systems AI翻译
  作者：Hadizadeh Kafash, Sahand; Ruths, Jusin
  作者单位：University of Texas System; University of Texas Dallas; University of Texas System; University of Texas Dallas
  摘要：In this article, we present a convex optimization framework to verify the reachability of a desired set for discrete-time linear time-invariant systems. Given elliptically bounded inputs, the set of reachable states in N time steps is the Minkowski sum of a finite number of ellipsoids. We formulate the inclusion verification problem as a chain of constraints in the form of linear matrix inequalities. As the time horizon grows, the number of constraints becomes unwieldy, and we present a techni...
• Trajectory Tracking of Underactuated VTOL Aerial Vehicles With Unknown System Parameters Via IRL AI翻译
  作者：Li, Shaobao; Durdevic, Petar; Yang, Zhenyu
  作者单位：Aalborg University
  摘要：This article studies the optimal control policy learning for underactuated vertical take-off and landing (VTOL) aerial vehicles subject to the unknown mass and inertia matrix. A novel off-policy integral reinforcement learning (IRL) scheme is presented for simultaneously unknown parameter identification and optimal trajectory tracking. In the outer loop of the VTOL vehicles, a novel off-policy IRL scheme is proposed, where the fixed control policy for data generation is chosen to be different ...
• Scheduling and Robust Invariance in Networked Control Systems AI翻译
  作者：Bahraini, Masoud; Zanon, Mario; Falcone, Paolo; Colombo, Alessandro
  作者单位：Chalmers University of Technology; IMT School for Advanced Studies Lucca; Universita di Modena e Reggio Emilia; Polytechnic University of Milan
  摘要：In networked control systems, impairments of the communication channel can be disruptive to stability and performance. In this article, we consider the problem of scheduling the access to limited communication resources for a number of decoupled systems subject to state and input constraints, whose loops need to be closed over the network. The schedule must be designed to robustly preserve the invariance property of each system, which, in turn, guarantees constraint satisfaction. To that end, ...
• Dynamic Multivariable Algebraic Loop Solver for Input-Constrained Control AI翻译
  作者：Adegbege, Ambrose Adebayo; Levenson, Richard M.
  作者单位：College of New Jersey
  摘要：We consider a gradient-like system for real-time implementation of multivariable algebraic loops arising in input-constrained control problems. Using results from mathematical programming, we establish global asymptotic convergence under a less stringent condition as compared to existing techniques. We comment on the application of the gradient-like system in antiwindup control implementation where the closed-loop can also be interpreted within the framework of singularly perturbed systems. Th...
• Performance Optimization via Sequential Processing for Nonlinear State Estimation of Noisy Systems AI翻译
  作者：Battilotti, Stefano
  作者单位：Sapienza University Rome
  摘要：We propose a framework for designing observers for noisy nonlinear systems with global convergence properties and performing robustness and noise sensitivity. This framework comes out from the combination of a state norm estimator with a chain of filters, adaptively tuned by the state norm estimator. The state estimate is sequentially processed through the chain of filters. Each filter contributes to improving, by a certain amount, the estimation error performances of the previous filter in te...