-
作者：Carnevale, Guido; Camisa, Andrea; Notarstefano, Giuseppe
作者单位：University of Bologna
摘要：This article focuses on an online version of the emerging distributed constrained aggregative optimization framework, which is particularly suited for applications arising in cooperative robotics. Agents in a network want to minimize the sum of local cost functions, each one depending both on a local optimization variable, subject to a local constraint, and on an aggregated version of all the variables (e.g., the mean). We focus on a challenging online scenario in which the cost, the aggregati...
-
作者：Zhang, Dan; Deng, Chao; Feng, Gang
作者单位：Zhejiang University of Technology; Nanjing University of Posts & Telecommunications; City University of Hong Kong
摘要：The resilient cooperative output regulation problem for a class of uncertain nonlinear multiagent systems (MASs) under denial-of-service (DoS) attacks is addressed in this article. This is the first attempt to investigate the cooperative output regulation problem for nonlinear MASs under DoS attacks, and a novel distributed control scheme consisting of a resilient distributed observer and a distributed adaptive controller is proposed. Specifically, a novel resilient distributed observer in the...
-
作者：Chi, Ronghu; Li, Huaying; Shen, Dong; Hou, Zhongsheng; Huang, Biao
作者单位：Qingdao University of Science & Technology; Renmin University of China; Qingdao University; University of Alberta
摘要：In this article, an indirect adaptive iterative learning control (iAILC) scheme is proposed for both linear and nonlinear systems to enhance the P-type controller by learning from set points. An adaptive mechanism is included in the iAILC method to regulate the learning gain using input-output measurements in real time. An iAILC method is first designed for linear systems to improve control performance by fully utilizing model information if such a linear model is known exactly. Then, an itera...
-
作者：Qi, Wenhai; Zong, Guangdeng; Hou, Yakun; Chadli, Mohammed
作者单位：Qufu Normal University; Chengdu University; Tiangong University; Universite Paris Saclay
摘要：This article is devoted to the discrete-time sliding mode control (DSMC) for nonlinear semi-Markovian switching systems (S-MSSs). Motivated by the fact that the complete information of the semi-Markov Kernel is difficult to be obtained in practical applications, it is recognized to be partly unknown as the most common mean. By utilizing the prior information of the sojourn-time upper bound for each switching mode, sufficient conditions under the equivalent DSMC law are proposed for the mean sq...
-
作者：Wang, Xuan; Mou, Shaoshuai; Anderson, Brian D. O.
作者单位：George Mason University; Purdue University System; Purdue University; Australian National University; Hangzhou Dianzi University
摘要：Inspired and underpinned by the idea of integral feedback, a distributed constant gain algorithm is proposed for multiagent networks to solve convex optimization problems with local linear constraints. Assuming agent interactions are modeled by an undirected graph, the algorithm is capable of achieving the optimum solution with an exponential convergence rate. Furthermore, inherited from the beneficial integral feedback, the proposed algorithm has attractive requirements on communication bandw...
-
作者：Zeng, Xianlin; Lei, Jinlong; Chen, Jie
作者单位：Beijing Institute of Technology; Tongji University
摘要：This article develops a continuous-time primal-dual accelerated method with an increasing damping coefficient for a class of convex optimization problems with affine equality constraints. This article analyzes critical values for parameters in the proposed method and prove that the rate of convergence in terms of the duality gap function is O( 1/t(2)) by choosing suitable parameters. As far as we know, this is the first continuous-time primaldual accelerated method that can obtain the optimal ...
-
作者：Zhao, Wenxiao; Weyer, Erik; Yin, George; Dong, Daoyi; Zhang, Yahui; Shen, Tielong
作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; University of Melbourne; University of Connecticut; University of New South Wales Sydney; Yanshan University; Sophia University
摘要：In this article, adaptive regulation of block-oriented nonlinear systems, i.e., Hammerstein and Wiener systems, with binary-valued measurements of the regulation errors is considered. Compared with the classical framework for stochastic adaptive control, the new feature here is that only binary-valued observations of regulation errors are available to the controller. An adaptive regulator based on the stochastic approximation algorithm is proposed and it is proved that the regulator is optimal...
-
作者：Singh, Navjot; Data, Deepesh; George, Jemin; Diggavi, Suhas
作者单位：University of California System; University of California Los Angeles; United States Department of Defense; United States Army; US Army Research, Development & Engineering Command (RDECOM); US Army Research Laboratory (ARL)
摘要：In this article, we propose and analyze SParsified Action Regulated Quantized-Stochastic Gradient Descent (SPARQ-SGD), a communication-efficient algorithm for decentralized training of large-scale machine learning models over a graph with $n$ nodes, where communication efficiency is achieved using compressed exchange of local model parameters among neighboring nodes, which is triggered only when an event (a locally computable condition) is satisfied. Specifically, in SPARQ-SGD, each node takes...
-
作者：Cai, Mingyu; Xiao, Shaoping; Li, Zhijun; Kan, Zhen
作者单位：Lehigh University; University of Iowa; Chinese Academy of Sciences; University of Science & Technology of China, CAS
摘要：This paper studies optimal motion planning subject to motion and environment uncertainties. By modeling the system as a probabilistic labeled Markov decision process (PL-MDP), the control objective is to synthesize a finite-memory policy, under which the agent satisfies complex high-level tasks expressed as linear temporal logic (LTL) with desired satisfaction probability. In particular, the cost optimization of the trajectory that satisfies infinite horizon tasks is considered, and the trade-...
-
作者：Massambone, Rafael; Costa, Eduardo Fontoura; Helou, Elias Salomao
作者单位：Universidade de Sao Paulo
摘要：In this article, a stochastic incremental subgradient algorithm for the minimization of a sum of convex functions is introduced. The method sequentially uses partial subgradient information, and the sequence of partial subgradients is determined by a general Markov chain. This makes it suitable to be used in networks, where the path of information flow is stochastically selected. We prove convergence of the algorithm to a weighted objective function, where the weights are given by the Cesaro l...
