9期

最新文章

• Fault-Tolerant Funnel Control for Uncertain Linear Systems AI翻译
  作者：Berger, Thomas
  作者单位：University of Paderborn
  摘要：We study adaptive fault-tolerant tracking control for uncertain linear systems. Based on recent results in funnel control, and the time-varying Byrnes-Isidori form, we develop a low-complexity model-free controller that achieves prescribed performance of the tracking error for any given sufficiently smooth reference signal. Within the considered system class, we allow for more inputs than outputs as long as a certain redundancy of the actuators is satisfied. An important role in the controller...
• A Gauss-Newton-Like Hessian Approximation for Economic NMPC AI翻译
  作者：Zanon, Mario
  作者单位：IMT School for Advanced Studies Lucca
  摘要：Economic model predictive control (EMPC) has recently become popular because of its ability to control constrained nonlinear systems while explicitly optimizing a prescribed performance criterion. Large performance gains have been reported for many applications and closed-loop stability has been recently investigated. However, computational performance still remains an open issue and only few contributions have proposed real-time algorithms tailored to EMPC. We perform a step towards computati...
• A Dynamic Gain-Based Saturation Control Strategy for Feedforward Systems With Long Delays in State and Input AI翻译
  作者：Sun, Jiwei; Lin, Wei
  作者单位：Dongguan University of Technology; University System of Ohio; Case Western Reserve University
  摘要：This article addresses the problem of global state regulation with stability by delay-free feedback for feedforward systems with large delays in both state and input. A gain-based nested saturation control strategy is developed to treat delays in the chain of integrators, state, and input simultaneously. It is shown that global state regulation with stability is possible by a delay-free, gain-based nested saturation compensator whose gain is updated dynamically. The effectiveness of the gain-b...
• Boundary Control of Nonlinear ODE/Wave PDE Systems With a Spatially Varying Propagation Speed AI翻译
  作者：Cai, Xiushan; Diagne, Mamadou
  作者单位：Hubei Normal University; Zhejiang Normal University; Rensselaer Polytechnic Institute
  摘要：We consider the boundary control of a nonlinear ordinary differential equation (ODE) actuated through a wave equation whose propagation speed is spatially varying. The ODE state is driven by the uncontrolled boundary of the wave equation. We design a nonlinear backstepping compensator to enable global asymptotic stability of the closed-loop system. We deduce the controller design and the stability proof by introducing a two-step backstepping transformation. The first transformation recasts the...
• Resilient Control of Cyber-Physical System Using Nonlinear Encoding Signal Against System Integrity Attacks AI翻译
  作者：Joo, Youngjun; Qu, Zhihua; Namerikawa, Toru
  作者单位：LG Corporation; LG Electronics; State University System of Florida; University of Central Florida; Keio University
  摘要：In this article, we propose an attack-resilient control structure for a cyber-physical system (CPS) to enhance the CPS security against stealthy system integrity attacks that manipulate the state of the physical plant while undetected. With the help of nonlinear encoding/decoding components, the proposed structure can detect stealthy attacks and preserve the nominal performance without considering attacks. Meanwhile, for avoiding the eavesdropping of transmitted signals used to synchronize enc...
• Taylor Moment Expansion for Continuous-Discrete Gaussian Filtering AI翻译
  作者：Zhao, Zheng; Karvonen, Toni; Hostettler, Roland; Sarkka, Simo
  作者单位：Aalto University; Alan Turing Institute; Uppsala University
  摘要：This article is concerned with Gaussian filtering in nonlinear continuous-discrete state-space models. We propose a novel Taylor moment expansion (TME) Gaussian filter, which approximates the moments of the stochastic differential equation with a temporal Taylor expansion. Differently from classical linearization or Ito-Taylor approaches, the Taylor expansion is formed for the moment functions directly and in time variable, not by using a Taylor expansion on the nonlinear functions in the mode...
• Observation for Markov Jump Piecewise-Affine Systems With Admissible Region-Switching Paths AI翻译
  作者：Ning, Zepeng; Zhang, Lixian; Feng, Gang; Mesbah, Ali
  作者单位：Harbin Institute of Technology; University of California System; University of California Berkeley; City University of Hong Kong
  摘要：The article investigates the problem of state observation for discrete-time Markov jump piecewise-affine (PWA) systems, which cover both Markov jump systems and traditional PWA systems as two special classes. A new method for determining the admissible region-switching paths between adjacent time instants is proposed for both the plant state and the estimator state, so that both the computation cost and the conservatism of the theoretical results are reduced. To analyze the mean-square stabili...
• Real-Time Scheduling Based on Nonblocking Supervisory Control of State-Tree Structures AI翻译
  作者：Wang, Xi; Li, Zhiwu; Wonham, W. M.
  作者单位：Xidian University; University of Erlangen Nuremberg; Macau University of Science & Technology; University of Toronto
  摘要：This article presents a novel framework for the modeling and scheduling of real-time systems (RTS) processing both sporadic and (multiperiod) periodic tasks, based on nonblocking supervisory control of state-tree structures. Instead of assigning static priorities, a real-time scheduling mechanism, namely priority-free conditionally preemptive scheduling, is used to describe the preemption relation among the tasks processed in an RTS. As a dynamic priority scheduling mechanism, partially preemp...
• A Fully Probabilistic Design for Tracking Control for Stochastic Systems With Input Delay AI翻译
  作者：Herzallah, Randa
  作者单位：Aston University
  摘要：This article studies model reference adaptive control (MRAC) for a class of stochastic discrete time control systems with time delays in the control input. In particular, a unified fully probabilistic control framework is established to develop the solution to the MRAC, where the controller is the minimizer of the Kullback-Leibler divergence between the actual and desired joint probability density functions of the tracking error and the controller. The developed framework is quite general, whe...
• A New Approach to Distributed Hypothesis Testing and Non-Bayesian Learning: Improved Learning Rate and Byzantine Resilience AI翻译
  作者：Mitra, Aritra; Richards, John A.; Sundaram, Shreyas
  作者单位：Purdue University System; Purdue University; United States Department of Energy (DOE); Sandia National Laboratories
  摘要：We study a setting where a group of agents, each receiving partially informative private signals, seek to collaboratively learn the true underlying state of the world (from a finite set of hypotheses), which generates their joint observation profiles. To solve this problem, we propose a distributed learning rule that differs fundamentally from existing approaches, in that it does not employ any form of belief-averaging. Instead, agents update their beliefs based on a min-rule. Under standard a...