IEEE Transactions on Automatic Control

最新文章

• Dynamic Droop Control in Low-Inertia Power Systems AI翻译
  作者：Jiang, Yan; Pates, Richard; Mallada, Enrique
  作者单位：Johns Hopkins University; Lund University
  摘要：A widely embraced approach to mitigate the dynamic degradation in low-inertia power systems is to mimic generation response using grid-connected inverters to restore the stiffness of the grid. In this article, we seek to challenge this approach and advocate for a principled design based on a systematic analysis of the performance trade-offs of inverter-based frequency control. With this aim, we perform a qualitative and quantitative study comparing the effect of conventional control strategies...
• L2-Gain Analysis of Periodic Event-Triggered Control and Self-Triggered Control Using Lifting AI翻译
  作者：Strijbosch, Nard; Dullerud, Geir E.; Teel, Andrew R.; Heemels, W. P. M. H.
  作者单位：Eindhoven University of Technology; University of Illinois System; University of Illinois Urbana-Champaign; University of California System; University of California Santa Barbara
  摘要：We analyze the stability, and L-2-gain properties of a class of hybrid systems that exhibit time-varying linear flow dynamics, periodic time-triggered jumps, and arbitrary nonlinear jump maps. This class of hybrid systems encompasses periodic event-triggered control, self-triggered control, and networked control systems including time-varying communication delays. New notions on the stability, and contractivity (L-2-gain strictly smaller than 1) from the beginning of the flow, and from the end...
• Synthesis of Maximally Permissive Supervisors for Nondeterministic Discrete Event Systems With Nondeterministic Specifications AI翻译
  作者：Takai, Shigemasa
  作者单位：University of Osaka
  摘要：In this article, we consider the problem of synthesizing a nondeterministic supervisor for the plant and the specification modeled as nondeterministic automata. A similarity control problem requires us to synthesize a supervisor such that the supervised plant is simulated by the specification. Ideally, the synthesized supervisor should be as permissive as possible. We develop a method for synthesizing a maximally permissive supervisor that solves the similarity control problem.
• A Generalized Framework for Simultaneous Long-Short Feedback Trading AI翻译
  作者：O'Brien, Joseph D.; Burke, Mark E.; Burke, Kevin
  作者单位：University of Limerick
  摘要：We present a generalization of the simultaneous long-short (SLS) trading strategy described in recent control literature wherein we allow for different parameters across the short and long sides of the controller; we refer to this new strategy as generalized SLS (GSLS). Furthermore, we investigate the conditions under which positive gain can be assured within the GSLS setup for both deterministic stock price evolution and geometric Brownian motion. In contrast to existing literature in this ar...
• Distributed Newton's Method for Network Cost Minimization AI翻译
  作者：Cao, Xuanyu; Liu, K. J. Ray
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University System of Maryland; University of Maryland College Park
  摘要：In this article, we examine a novel generic network cost minimization problem, in which every node has a local decision vector to optimize. Each node incurs a cost associated with its decision vector, while each link incurs a cost related to the decision vectors of its two end nodes. All nodes collaborate to minimize the overall network cost. The formulated network cost minimization problem has broad applications in distributed signal processing and control, in which the notion of link costs o...
• A Computationally Efficient Robust Model Predictive Control Framework for Uncertain Nonlinear Systems AI翻译
  作者：Koehler, Johannes; Soloperto, Raffaele; Mueller, Matthias A.; Allgoewer, Frank
  作者单位：University of Stuttgart; Leibniz University Hannover
  摘要：In this article, we present a nonlinear robust model predictive control (MPC) framework for general (state and input dependent) disturbances. This approach uses an online constructed tube in order to tighten the nominal (state and input) constraints. To facilitate an efficient online implementation, the shape of the tube is based on an offline computed incremental Lyapunov function with a corresponding (nonlinear) incrementally stabilizing feedback. Crucially, the online optimization only impl...
• An Augmented Lagrangian for Optimal Control of DAE Systems: Algorithm and Properties AI翻译
  作者：Aguiar, Marco Aurelio; Camponogara, Eduardo; Foss, Bjarne
  作者单位：Universidade Federal de Santa Catarina (UFSC); Norwegian University of Science & Technology (NTNU)
  摘要：This article proposes a relax-and-discretize approach for optimal control of continuous-time differential algebraic systems. It works by relaxing the algebraic equations and penalizing the violation into the objective function using the augmented Lagrangian, which converts the original problem into a sequence of optimal control problems (OCPs) of ordinary differential equations (ODEs). The relax-and-discretize approach brings about flexibility, by allowing the OCPs of ODEs to be solved by the ...
• On Practical Stability Preservation Under Fast Sampling and Accurate Quantization of Feedbacks for Nonlinear Time-Delay Systems AI翻译
  作者：Di Ferdinando, Mario; Pepe, Pierdomenico; Borri, Alessandro
  作者单位：University of L'Aquila; Consiglio Nazionale delle Ricerche (CNR); Istituto di Analisi dei Sistemi ed Informatica Antonio Ruberti (IASI-CNR)
  摘要：In this article, we deal with the problem of stabilizing a nonlinear system with state-delays by means of quantized sampled-data state feedback control laws. Quantization in the state measurements and in the input signal are simultaneously considered. Fully nonlinear (i.e., possibly nonaffine in the control) time-delay systems are studied. Sufficient conditions are provided such that suitably fast sampling and accurate quantization of the state feedback at hand yield semiglobal practical stabi...
• Feedback Stabilization of a Class of Diagonal Infinite-Dimensional Systems With Delay Boundary Control AI翻译
  作者：Lhachemi, Hugo; Prieur, Christophe
  作者单位：University College Dublin; Communaute Universite Grenoble Alpes; Institut National Polytechnique de Grenoble; Universite Grenoble Alpes (UGA); Centre National de la Recherche Scientifique (CNRS)
  摘要：This article studies the boundary feedback stabilization of a class of diagonal infinite-dimensional boundary control systems. In the studied setting, the boundary control input is subject to a constant delay while the open-loop system might exhibit a finite number of unstable modes. The proposed control design strategy consists of two main steps. First, a finite-dimensional subsystem is obtained by truncation of the original infinite-dimensional system (IDS) via modal decomposition. It includ...
• Push-Pull Gradient Methods for Distributed Optimization in Networks AI翻译
  作者：Pu, Shi; Shi, Wei; Xu, Jinming; Nedic, Angelia
  作者单位：Shenzhen Research Institute of Big Data; The Chinese University of Hong Kong, Shenzhen; Princeton University; Zhejiang University; Arizona State University; Arizona State University-Tempe
  摘要：In this article, we focus on solving a distributed convex optimization problem in a network, where each agent has its own convex cost function and the goal is to minimize the sum of the agents' cost functions while obeying the network connectivity structure. In order to minimize the sum of the cost functions, we consider new distributed gradient-based methods where each node maintains two estimates, namely an estimate of the optimal decision variable and an estimate of the gradient for the ave...