IEEE Transactions on Automatic Control

最新文章

• Convex Hulls of Reachable Sets AI翻译
  作者：Lew, Thomas; Bonalli, Riccardo; Pavone, Marco
  作者单位：Toyota Motor Corporation; Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS); Stanford University
  摘要：We study the convex hulls of reachable sets of nonlinear systems with bounded disturbances and uncertain initial conditions. Reachable sets play a critical role in control, but remain notoriously challenging to compute, and existing overapproximation tools tend to be conservative or computationally expensive. In this work, we characterize the convex hulls of reachable sets as the convex hulls of solutions of an ordinary differential equation with initial conditions on the sphere. This finite-d...
• Algorithm to Find New Identifiable Reparameterizations of Parameteric Rational ODE Models AI翻译
  作者：Meshkat, Nicolette; Ovchinnikov, Alexey; Scanlon, Thomas
  作者单位：Santa Clara University; City University of New York (CUNY) System; City University of New York (CUNY) System; University of California System; University of California Berkeley
  摘要：Structural identifiability concerns the question of which unknown parameters of a model can be recovered from (perfect) input-output (IO) data. If all of the parameters of a model can be recovered from data, then the model is said to be identifiable. However, in many models, there are parameters that can take on an infinite number of values but yield the same input-output data. In this case, those parameters and the model are called unidentifiable. The question is then what to do with an unide...
• Trajectory Tracking of AAVs Based on Rodrigues Parameter AI翻译
  作者：Wu, Zhaojing
  作者单位：Yantai University
  摘要：The problem of trajectory tracking of autonomous aerial vehicles (AAVs) is researched by the aid of Rodrigues parameter (RP). With the attitude planner being designed, the underactuated translational system is transformed to the full-actuated form, and rotational error dynamics based-on RP is obtained. To avoid unwinding phenomenon, a continuous nested saturation controller is constructed such that the input-to-state stability of the closed-loop error system is obtained, which is equivalent to...
• Delayed Pinning Control for Synchronization of Dynamical Networks AI翻译
  作者：Zhu, Shuaibing; Li, Feng; Deng, Zhenhua; Lu, Jinhu
  作者单位：Hunan Normal University; Anhui University of Technology; Central South University; Beihang University
  摘要：Although pinning control of dynamical networks with or without delay has been well explored in the past two decades, little attention has been paid to the delay originated from pinning control itself. This article investigates the delayed pinning control scheme for lag synchronization and lag quasi-synchronization of dynamical networks. Two pinning control schemes with uniform delay and nonuniform delays are proposed, which are more practical than the widely used delay-free pinning control sch...
• Distributional Uncertainty Propagation via Optimal Transport AI翻译
  作者：Aolaritei, Liviu; Lanzetti, Nicolas; Chen, Hongruyu; Dorfler, Florian
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
  摘要：This article addresses the limitations of standard uncertainty models, i.e., robust (norm-bounded) and stochastic (one fixed distribution, e.g., Gaussian), and proposes to model uncertainty via optimal transport (OT) ambiguity sets. These constitute a very rich uncertainty model, which enjoys many desirable geometrical, statistical, and computational properties, and which naturally generalizes both robust and stochastic models, and captures many additional real-world uncertainty phenomena (e.g...
• Multiple Model Reference Adaptive Control With Blending for Nonsquare Multivariable Systems AI翻译
  作者：Lovi, Alex; Fidan, Baris; Nielsen, Christopher
  作者单位：University of Waterloo; University of Waterloo
  摘要：In this article, we develop a multiple model reference adaptive controller (MMRAC) with blending. The systems under consideration are Non square, i.e., the num-ber of inputs is not equal to the number of states; multi-input, linear, time-invariant with uncertain parameters that lie inside of a known, compact, and convex set. Moreover, the full state of the plant is available for feedback. A multiple model online identification scheme for the plant's state and input matrices is developed that g...
• Dynamic-High-Gain-Based Decentralized Optimal Fault-Tolerant Control for a Class of Interconnected Nonlinear Systems AI翻译
  作者：Yang, Xinyu; Puig, Vicenc; Wang, Xingjian; Wang, Shaoping; Sun, Chen; Zhang, Yixin
  作者单位：Beihang University; Consejo Superior de Investigaciones Cientificas (CSIC); Universitat Politecnica de Catalunya; CSIC - Institut de Robotica i Informatica Industrial (IRII); Beihang University; Beihang University; Tianmushan Lab; China University of Mining & Technology
  摘要：In this article, a dynamic high-gain-based decentralized optimal fault-tolerant control (FTC) strategy for a class of strong interconnected systems with unknown actuator faults is proposed. The interactions considered are bounded by some functions that depend on all subsystems' states. A two-layer control framework is presented for each subsystem to steer its tracking error asymptotically to zero. In the upper layer, an error optimizer is designed to generate optimal error trajectory based on ...
• Safety-Critical Learning of Robot Control With Temporal Logic Specifications AI翻译
  作者：Cai, Mingyu; Vasile, Cristian-Ioan
  作者单位：University of California System; University of California Riverside; Lehigh University
  摘要：Reinforcement learning (RL) is a promising control approach in many scenarios. However, safety-critical applications are still a challenge due to lack of safety guarantees during exploration and subsequent deployment. The learning problem becomes even more difficult for complex tasks with temporal and logical constraints. In this article, we introduce a modular deep RL architecture as a control framework to satisfy complex tasks specified using linear temporal logic (LTL). To enhance safety, w...
• Cooperative Trajectory Tracking of Heterogeneous Networks by Distributed Learning AI翻译
  作者：Meng, Deyuan; Zhang, Jingyao
  作者单位：Beihang University; Beihang University
  摘要：This article presents a distributed learning approach to achieve the high-precision cooperative trajectory tracking tasks for heterogeneous networks at all time in the presence of changing topologies. An updating law of distributed learning is proposed by leveraging the cooperative tracking error trajectories of agents at all time samples, thanks to which a monotonic convergence result is established for heterogeneous networks of linear agents without iteration-varying uncertainties. When cons...
• Self-Triggered Stabilization of Contracting Systems Under Quantization AI翻译
  作者：Wakaiki, Masashi
  作者单位：Kobe University
  摘要：We propose self-triggered control schemes for nonlinear systems with quantized state measurements. Our focus lies on scenarios where both the controller and the self-triggering mechanism receive only the quantized state at each sampling time. We assume that the ideal closed-loop system without quantization or self-triggered sampling is contracting. Moreover, an upper bound on the growth rate of the open-loop system is assumed to be known. We present two control schemes that achieve closed-loop...