IEEE Transactions on Automatic Control

最新文章

• Time-Domain Sensitivity of the Tracking Error AI翻译
  作者：O'Neil, Sean; Schirmer, Sophie; Langbein, Frank C.; Weidner, Carrie A.; Jonckheere, Edmond A.
  作者单位：University of Southern California; Swansea University; Cardiff University; University of Bristol
  摘要：A strictly time-domain. formulation of the log-sensitivity of the error signal to structured plant uncertainty is presented and analyzed through simple but representative classical and quantum systems. Results demonstrate that across a wide range of physical systems, maximization of performance (minimization of the error signal) asymptotically or at a specific time comes at the cost of increased log-sensitivity, implying a time-domain constraint analogous to the frequency-domain identity S(s) ...
• Dominant Mixed Feedback Design for Stable Oscillations AI翻译
  作者：Che, Weiming; Forni, Fulvio
  作者单位：University of Cambridge
  摘要：We present a design framework that combines positive and negative feedback for robust stable oscillations in closed loop. The design is initially based on graphical methods, to guide the selection of the overall strength of the feedback (gain) and of the relative proportion of positive and negative feedback (balance). The design is then generalized via linear matrix inequalities. The goal is to guarantee robust oscillations to bounded dynamic uncertainties and to extend the approach to passive...
• Backstepping Control of an Underactuated Hyperbolic-Parabolic Coupled PDE System AI翻译
  作者：Chen, Guangwei; Vazquez, Rafael; Liu, Zhitao; Su, Hongye
  作者单位：Beijing University of Technology; University of Sevilla; Zhejiang University
  摘要：This article considers a class of hyperbolic-parabolic partial differential equation (PDE) system with some interior mixed-coupling terms, a rather unexplored family of systems. The family of systems we explore contains several interior-coupling terms, which makes controller design more challenging. Our goal is to design a boundary controller to exponentially stabilize the coupled system. For that, we propose a controller whose design is based on the backstepping method. Under this controller,...
• Optimal Control of Probability on a Target Set for Continuous-Time Markov Chains AI翻译
  作者：Ma, Chenglin; Zhao, Huaizhong
  作者单位：Shandong University; Durham University; Shandong University
  摘要：In this article, a stochastic optimal control problem is considered for a continuous-time Markov chain taking values in a denumerable state space over a fixed finite horizon. The optimality criterion is the probability that the process remains in a target set before and at a certain time. The optimal value is a superadditive capacity of target sets. Under some minor assumptions for the controlled Markov process, we establish the dynamic programming principle, based on which we prove that the v...
• Scalable Computation of Robust Control Invariant Sets of Nonlinear Systems AI翻译
  作者：Schaefer, Lukas; Gruber, Felix; Althoff, Matthias
  作者单位：Technical University of Munich; Bosch
  摘要：Ensuring robust constraint satisfaction for an infinite-time horizon is a challenging, yet crucial task when deploying safety-critical systems. In this article, we address this issue by synthesizing robust control invariant sets of perturbed nonlinear sampled-data systems. This task can be encoded as a nonconvex program that we approximate by a tailored, computationally efficient successive convexification algorithm. Based on the zonotopic representation of invariant sets, we obtain an updated...
• Distance-Based Formation Tracking of Single- and Double-Integrator Agents AI翻译
  作者：Vu, Hieu Minh; Trinh, Minh Hoang; Tran, Quoc Van; Ahn, Hyo-Sung
  作者单位：Hanoi University of Science & Technology (HUST); Hanoi University of Science & Technology (HUST); Gwangju Institute of Science & Technology (GIST)
  摘要：This article studies the distance-based formation tracking problem of a group of agents with a leader-follower topology. It is assumed that the desired formation is minimally infinitesimally rigid and the agents in the formation are classified as leaders and followers. The leaders are moving in the space and their positions determine a time-varying target formation, which may differ from the desired formation by a translation and a rotation. The followers, which can sense the local displacemen...
• Distributed State Estimation Under Jointly Connected Switching Networks: Continuous-Time Linear Systems and Discrete-Time Linear Systems AI翻译
  作者：Zhang, Lan; Lu, Maobin; Deng, Fang; Chen, Jie
  作者单位：Beijing Institute of Technology; Beijing Institute of Technology; Beijing Institute of Technology; Tongji University
  摘要：In this article, we address the distributed state estimation problem for both continuous-time linear time-invariant (LTI) systems and discrete-time LTI systems under switching networks. The observed system is jointly observable, i.e., each agent can only access a part of the measurement output of the observed system and cannot recover the full state by itself. The full state estimation has to be achieved by network communication of neighboring agents. In contrast to existing works, the salient...
• Learning Robust Data-Based LQG Controllers From Noisy Data AI翻译
  作者：Liu, Wenjie; Wang, Gang; Sun, Jian; Bullo, Francesco; Chen, Jie
  作者单位：Beijing Institute of Technology; University of California System; University of California Santa Barbara; University of California System; University of California Santa Barbara; Tongji University
  摘要：This article addresses the joint state estimation and control problems for unknown linear time-invariant systems subject to both process and measurement noise. The aim is to redesign the linear quadratic Gaussian (LQG) controller-based solely on data. The LQG controller comprises a linear quadratic regulator (LQR) and a steady-state Kalman observer; while the data-based LQR design problem has been previously studied, constructing the Kalman gain and the LQG controller from noisy data presents ...
• Distributed Nash Equilibrium Seeking for Uncertain Euler-Lagrange Systems Over Jointly Strongly Connected Networks AI翻译
  作者：Liu, Zhaocong; Huang, Jie
  作者单位：Chinese University of Hong Kong
  摘要：In this article, we first construct a control law to solve the distributed Nash equilibrium (NE) seeking problem for games with multiple players whose actions are governed by a class of uncertain Euler-Lagrange (EL) systems. Then, we further consider the same problem with the EL systems subject to trigonometric polynomial disturbances with arbitrarily unknown amplitudes, initial phases, and frequencies. We integrate the internal model principle and the adaptive control technique to deal with s...
• Learning Optimal Strategies for Temporal Tasks in Stochastic Games AI翻译
  作者：Bozkurt, Alper Kamil; Wang, Yu; Zavlanos, Michael M.; Pajic, Miroslav
  作者单位：Duke University; State University System of Florida; University of Florida
  摘要：Synthesis from linear temporal logic (LTL) specifications provides assured controllers for systems operating in stochastic and potentially adversarial environments. Automatic synthesis tools, however, require a model of the environment to construct controllers. In this work, we introduce a model-free reinforcement learning (RL) approach to derive controllers from given LTL specifications even when the environment is completely unknown. We model the problem as a stochastic game (SG) between the...