IEEE Transactions on Automatic Control

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• The Curious Case of Integrator Reach Sets, Part I: Basic Theory AI翻译
  作者：Haddad, Shadi; Halder, Abhishek
  作者单位：University of California System; University of California Santa Cruz
  摘要：This is the first of a two part paper investigating the geometry of the integrator reach sets, and the applications thereof. In this Part I, assuming box-valued input uncertainties, we establish that this compact convex reach set is semialgebraic, translated zonoid, and not a spectrahedron. We derive the parametric as well as the implicit representation of the boundary of this reach set. We also deduce the closed-form formula for the volume and diameter of this set, and discuss their scaling w...
• Distributed Design of Glocal Controllers via Hierarchical Model Decomposition AI翻译
  作者：Sasahara, Hampei; Ishizaki, Takayuki; Imura, Jun-ichi; Sandberg, Henrik; Johansson, Karl Henrik
  作者单位：Institute of Science Tokyo; Tokyo Institute of Technology; Royal Institute of Technology
  摘要：This article proposes a distributed design method of controllers with a glocal (global/local) information structure for large-scale network systems. The glocal controller of interest has a hierarchical structure, wherein a global subcontroller coordinates a set of disjoint local subcontrollers. The global subcontroller regulates interarea oscillations among subsystems, while local subcontrollers individually regulate intraarea oscillations of the respective subsystem. The distributed design of...
• Hybrid Nash Equilibrium Seeking Under Partial-Decision Information: An Adaptive Dynamic Event-Triggered Approach AI翻译
  作者：Xu, Wenying; Wang, Zidong; Hu, Guoqiang; Kurths, Jurgen
  作者单位：Southeast University - China; Brunel University; Nanyang Technological University; Potsdam Institut fur Klimafolgenforschung; Lobachevsky State University of Nizhni Novgorod
  摘要：This article is concerned with the hybridNash equilibrium (NE) seeking problem over a network in a partial-decision information scenario. Each agent has access to both its own cost function and local decision information of its neighbors. First, an adaptive gradient-based algorithm is constructed in a fully distributed manner with the guaranteed convergence to the NE, where the network communication is required. Second, in order to save communication cost, a novel event-triggered scheme, namel...
• Soft-Reset Control With Max-of-Quadratics Lyapunov Certificates AI翻译
  作者：Bertollo, Riccardo; Teel, Andrew R.; Zaccarian, Luca
  作者单位：University of Trento; University of California System; University of California Santa Barbara; Universite de Toulouse; Centre National de la Recherche Scientifique (CNRS)
  摘要：In this article, we further develop a novel control paradigm encoding the core behavior of a reset control system within a continuous-time feedback, described by a differential inclusion. A tuning knob allows adjusting how close the continuous-time feedback resembles the behavior of the underlying reset controller. The Lyapunov conditions that we derive naturally lead to a sum-of-squares formulation allowing for the design of max-of-quadratics Lyapunov certificates associated with polynomial m...
• Improving the Transient Times for Distributed Stochastic Gradient Methods AI翻译
  作者：Huang, Kun; Pu, Shi
  作者单位：The Chinese University of Hong Kong, Shenzhen; Shenzhen Research Institute of Big Data; The Chinese University of Hong Kong, Shenzhen; The Chinese University of Hong Kong, Shenzhen; Shenzhen Institute of Artificial Intelligence & Robotics for Society
  摘要：We consider the distributed optimization problem where n agents, each possessing a local cost function, collaboratively minimize the average of the n cost functions over a connected network. Assuming stochastic gradient information is available, we study a distributed stochastic gradient algorithm, called exact diffusion with adaptive stepsizes (EDAS) adapted from the Exact Diffusion method (Yuan et al., 2019) and NIDS (Li et al., 2019) and perform a nonasymptotic convergence analysis. We not ...
• Practical Learning-Tracking Framework Under Unknown Nonrepetitive Channel Randomness AI翻译
  作者：Shen, Dong
  作者单位：Renmin University of China
  摘要：In this study, we consider the learning-tracking problem for stochastic systems through unreliable communication channels. The channels suffer from both multiplicative and additive randomness subject to unknown probability distributions. The statistics of this randomness, such as mean and covariance, are nonrepetitive in the iteration domain. This nonrepetitive randomness introduces nonstationary contamination and drifts to the actual signals, yielding essential challenges in signal processing...
• Deep Neural Network-Based Approximate Optimal Tracking for Unknown Nonlinear Systems AI翻译
  作者：Greene, Max L.; Bell, Zachary I.; Nivison, Scott; Dixon, Warren E.
  作者单位：Johns Hopkins University; State University System of Florida; University of Florida
  摘要：The infinite horizon optimal tracking problem is solved for a deterministic, control-affine, unknown nonlinear dynamical system. A deep neural network (DNN) is updated in real time to approximate the unknown nonlinear system dynamics. The developed framework uses a multitimescale concurrent learning-based weight update policy, with which the output layer DNN weights are updated in real time, but the internal DNN features are updated discretely and at a slower timescale (i.e., with batch-like u...
• Adaptive Composite Online Optimization: Predictions in Static and Dynamic Environments AI翻译
  作者：Scroccaro, Pedro Zattoni; Kolarijani, Arman Sharifi; Esfahani, Peyman Mohajerin
  作者单位：Delft University of Technology
  摘要：In the past few years, online convex optimization (OCO) has received notable attention in the control literature thanks to its flexible real-time nature and powerful performance guarantees. In this article, we propose new step-size rules and OCO algorithms that simultaneously exploit gradient predictions, function predictions and dynamics, features particularly pertinent to control applications. The proposed algorithms enjoy static and dynamic regret bounds in terms of the dynamics of the refe...
• Nonlinear Stochastic Model Predictive Control: Existence, Measurability, and Stochastic Asymptotic Stability AI翻译
  作者：McAllister, Robert D.; Rawlings, James B.
  作者单位：University of California System; University of California Santa Barbara
  摘要：In this article, we establish a collection of new theoretical properties for nonlinear stochastic model predictive control (SMPC). Based on the concept of stochastic input-to-state stability (SISS), we define robust asymptotic stability in expectation (RASiE) and establish that nonlinear SMPC renders the origin of the closed-loop system RASiE. Moreover, we establish several new foundational results that have not been addressed in previous research. Specifically, we verify that, under basic reg...
• Sequential Detection of Replay Attacks AI翻译
  作者：Naha, Arunava; Teixeira, Andre; Ahlen, Anders; Dey, Subhrakanti
  作者单位：Uppsala University; Uppsala University
  摘要：One of the most studied forms of attacks on the cyber-physical systems is the replay attack. The statistical similarities of the replayed signal and the true observations make the replay attack difficult to detect. In this article, we address the problem of replay attack detection by adding watermarking to the control inputs and then perform resilient detection using cumulative sum (CUSUM) test on the joint statistics of the innovation signal and the watermarking signal, whereas existing work ...