11期

最新文章

• Dynamic Event-Triggered Impulsive Tracking Control of Strict-Feedback Nonlinear Systems: A Gain Scaling Approach AI翻译
  作者：Pan, Weihao; Zhang, Xianfu; Fan, Debao; Feng, Gang
  作者单位：Shandong University; City University of Hong Kong
  摘要：This note presents a gain scaling approach to the dynamic event-triggered impulsive tracking control problem for strict-feedback nonlinear systems. The nonlinear growth rate under consideration is allowed to contain a continuous function of the system output, and the problem has not been considered under the existing impulsive control framework. By constructing a state transformation, a novel dynamic event-triggered impulsive tracking controller is designed. It is proved that the proposed impu...
• Command Filter-Based Predefined Time Adaptive Control for Nonlinear Systems AI翻译
  作者：Sui, Shuai; Chen, C. L. Philip; Tong, Shaocheng
  作者单位：Liaoning University of Technology; South China University of Technology
  摘要：In this article, we study the predefined-time adaptive control problem for a class of strict-feedback nonlinear systems with parametric uncertainties and disturbances. A new practical predefined time stable (PPTS) criterion is first presented as the theoretical basis of predefined time control design, and then a new nonlinear command filter is designed. Based on the established PPTS criterion and backstepping control design technique, a command filter-based predefined time adaptive backsteppin...
• Semiglobal Fixed-Time State Estimation and Unknown Input Reconstruction via First-Order Sliding-Mode Observers With Delay AI翻译
  作者：Pilloni, Alessandro; Pisano, Alessandro; Usai, Elio
  作者单位：University of Cagliari
  摘要：This article addresses the state estimation and unknown input reconstruction in strongly observable linear systems under the so-called matching conditions. Our proposal extends previous approaches to predefined-time state estimation, which involved the use of a pair of time-delay observers, adapting them to the framework of sliding-mode observation in the presence of unknown inputs. As a result, a novel sliding-mode-based observation algorithm is developed, which exhibits desirable properties,...
• Nodal Consensus in Multiagent Systems With Edge Communications AI翻译
  作者：Rong, Lina; Jiang, Guo-Ping; Xu, Shengyuan
  作者单位：Nanjing University of Posts & Telecommunications; Nanjing University of Science & Technology
  摘要：In this article, we studies the nodal consensus in multiagent systems subject to edge communications. It is revealed that the edge communication can be modeled as perturbations to the nodal network, and the multiagent network is then equivalent to a feedback loop introducing a negative feedback element to the edge dynamics. In virtue of this, a two-layer network perspective is adopted in studying the nodal consensus, where it is shown that the behavior of edge communication is essentially an i...
• Scalable Synthesis of Safety Barrier Certificates for Networks of Stochastic Switched Systems AI翻译
  作者：Lavaei, Abolfazl; Frazzoli, Emilio
  作者单位：Newcastle University - UK; Swiss Federal Institutes of Technology Domain; ETH Zurich
  摘要：In this article, we propose a compositional scheme for the safety controller synthesis of stochastic switched networks with dwell-time conditions. The proposed framework is based on a notion of so-called transition subbarrier certificates constructed for each switched subsystem, by employing which one can compositionally synthesize safety controllers for interconnected networks over (in)finite time horizons. In our proposed scheme, we leverage dissipativity-type compositional conditions to com...
• Stability of Optimal Estimator With Unobservable Measurement Loss: The Unstable System Case AI翻译
  作者：Lin, Hong; Lam, James
  作者单位：Shenzhen Polytechnic University; University of Hong Kong
  摘要：We study the stability of the optimal estimator (OE) for an unstable system with unobservable measurement loss (UML). The results are twofold. 1) We obtain a necessary and sufficient stability condition: For an unstable UML system, there is a critical value such that the OE is stable with probability 1, if and only if the measurement-arrival rate is greater than this value. This value is identical to the critical value that determines the stability of the OE with observable measurement loss (O...
• Decision Function-Based Adaptive Control of Uncertain Systems Subject to Irregular Output Constraints AI翻译
  作者：Zhao, Kai; Song, Yongduan
  作者单位：Chongqing University
  摘要：While barrier Lyapunov function-based approach has been successfully used in adaptive control of uncertain systems with output/state constraints, it is nontrivial to use this method to deal with systems with irregular constraints (where the constraints may appear, disappear, or alternate during system operation). It is in fact an open interesting problem to develop a control method capable of coping with the irregular constraints uniformly. In this note, a unified adaptive control strategy is ...
• Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent AI翻译
  作者：Jing, Gangshan; Bai, He; George, Jemin; Chakrabortty, Aranya; Sharma, Piyush K.
  作者单位：Chongqing University; Oklahoma State University System; Oklahoma State University - Stillwater; North Carolina State University
  摘要：Recently introduced distributed zeroth-order optimization (ZOO) algorithms have shown their utility in distributed reinforcement learning (RL). Unfortunately, in the gradient estimation process, almost all of them require random samples with the same dimension as the global variable and/or require evaluation of the global cost function, which may induce high estimation variance for large-scale networks. In this paper, we propose a novel distributed zeroth-order algorithm by leveraging the netw...
• Regulation of Nonlinear Systems Subject to Uniform Output Quantization AI翻译
  作者：Castro, Rafael S.; Salton, Aurelio T.; Fu, Minyue; Isidori, Alberto
  作者单位：Universidade Federal do Rio Grande do Sul; Southern University of Science & Technology; Sapienza University Rome
  摘要：This article addresses the problem of controlling a nonlinear plant subject to uniformly quantized measurements to have its output track and/or reject a family of signals produced by some external generator. First, conditions based on passivity and the theory of output regulation are devised to achieve convergence of the quantized error, namely, the difference between the quantized output and the (artificially) quantized reference. Then, further conditions on the reference are shown such that ...
• Robust Reinforcement Learning for Risk-Sensitive Linear Quadratic Gaussian Control AI翻译
  作者：Cui, Leilei; Basar, Tamer; Jiang, Zhong-Ping
  作者单位：New York University; New York University Tandon School of Engineering; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：This article proposes a novel robust reinforcement learning framework for discrete-time linear systems with model mismatch that may arise from the sim-to-real gap. A key strategy is to invoke advanced techniques from control theory. Using the formulation of the classical risk-sensitive linear quadratic Gaussian control, a dual-loop policy optimization algorithm is proposed to generate a robust optimal controller. The dual-loop policy optimization algorithm is shown to be globally and uniformly...