Output regulation theory is an effective method for achieving accurate time-varying command following and can utilize adaptive internal models to follow arbitrary reference signals generated by an exosystem. However, ...
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作者：
Ouyang, JinhuaChen, XuMechatronics
Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States Mechatronics
Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States
We present a system identification method based on recursive least-squares (RLS) and coprime collaborative sensing, which can recover system dynamics from non-uniform temporal data. Focusing on systems with fast input...
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This paper develops and investigates a dual unscented Kalman filter (DUKF) for the joint nonlinear state and parameter identification of commercial adaptive cruise control (ACC) systems. Although the core functionalit...
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This paper explores the eco-driving problem of parallel hybrid electric vehicles, intended to drive a certain distance within a limited amount of time, where the longitudinal vehicle velocity and powertrain controls a...
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This paper explores the eco-driving problem of parallel hybrid electric vehicles, intended to drive a certain distance within a limited amount of time, where the longitudinal vehicle velocity and powertrain controls are optimized to minimize the fuel consumption. In particular, we incorporate Pontryagin's Minimum Principle (PMP) and singular control theory in an optimization framework to find the fuel-optimal velocity and power-split control policy for the prime mover and the electric machine with global optimality guarantees. In addition, we present reformulations and derivations, so that the same problem can be solved jointly using another framework based on convex optimization, with the same global optimality properties, employing methods originally derived for timeoptimal control of race cars. Thereby, we formally show the equivalence between the eco-driving and the racing problem. We showcase both our frameworks with numerical solutions, drawing three comparisons: First, we solve the velocity and power-split problem, both sequentially and jointly, using the PMP framework. We show that the latter can improve the fuel consumption by 2.6 %. Second, we benchmark the PMP and the convex framework by solving the joint problem with both methods and observe a discrepancy of 0.14% in terms of the resulting fuel energy consumption. Finally, in a numerical study addressing the performance of both methods individually, we observe that the efficiency of the PMP and the convex framework are strongly dependent on the stopping criteria and the discretization step size, respectively. Authors
Discrete event system(DES)models promote system engineering,including system design,verification,and *** advancement in manufacturing technology has endowed us to fabricate complex industrial ***,the adoption of advan...
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Discrete event system(DES)models promote system engineering,including system design,verification,and *** advancement in manufacturing technology has endowed us to fabricate complex industrial ***,the adoption of advanced modeling methodologies adept at handling complexity and scalability is ***,industrial systems are no longer quiescent,thus the intelligent operations of the systems should be dynamically specified in the *** this paper,the composition of the subsystem behaviors is studied to generate the complexity and scalability of the global system model,and a Boolean semantic specifying algorithm is proposed for generating dynamic intelligent operations in the *** traditional modeling approaches,the change or addition of specifications always necessitates the complete resubmission of the system model,a resource-consuming and error-prone *** with traditional approaches,our approach has three remarkable advantages:(i)an established Boolean semantic can be fitful for all kinds of systems;(ii)there is no need to resubmit the system model whenever there is a change or addition of the operations;(iii)multiple specifying tasks can be easily achieved by continuously adding a new ***,this general modeling approach has wide potential for future complex and intelligent industrial systems.
In this study, our main objective is to address the issue of sampled-data-based synchronization of complex networks subjected to stochastic scaling attacks using a looped-functional approach. To begin with, the design...
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Fatigue failure caused by vibration is the most common type of pipeline *** core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to be expl...
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Fatigue failure caused by vibration is the most common type of pipeline *** core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to be explored in the existing *** shell theory can better simulate the circumferential stress distribution,and thus the Mindlin-Reissner shell theory is used to model the *** this paper,the continuous pipeline system is combined with clamps through modal expansion for the first time,which realizes the coupling problem between a shell and a *** the Bouc-Wen model is used to simulate the nonlinear external force generated by a clamp,the nonlinear coupling characteristics of the system are effectively ***,the dynamic equation of the clamp-pipeline system is established according to the Lagrange energy *** on the resonance frequency and stress amplitude obtained from the experiment,the nonlinear parameters of the clamp are identified with the semi-analytical method(SAM)and particle swarm optimization(PSO)*** study provides a theoretical basis for the clamp-pipeline system and an efficient and universal solution for stress prediction and analysis of pipelines in engineering.
This article presents a comprehensive performance analysis of the step-climbing and passive rolling modes of a hexagon rolling mechanism with single-degree-of-freedom, based on its structural characteristics and the c...
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The paper considers the adaptive regulation for the Hammerstein and Wiener systems with event-triggered *** authors adopt a direct approach,i.e.,without identifying the unknown parameters and functions within the syst...
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The paper considers the adaptive regulation for the Hammerstein and Wiener systems with event-triggered *** authors adopt a direct approach,i.e.,without identifying the unknown parameters and functions within the systems,adaptive regulators are directly designed based on the event-triggered observations on the regulation *** adaptive regulators belong to the stochastic approximation algorithms and under moderate assumptions,the authors prove that the adaptive regulators are optimal for both the Hammerstein and Wiener systems in the sense that the squared regulation errors are asymptotically *** authors also testify the theoretical results through simulation studies.
Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpret...
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Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpretability.A promising approach to overcoming these challenges is to embed domain knowledge into the ML pipeline,enhancing the model with additional pattern *** this paper,we review the latest developments in PHM,encapsulated under the concept of Knowledge Driven Machine Learning(KDML).We propose a hierarchical framework to define KDML in PHM,which includes scientific paradigms,knowledge sources,knowledge representations,and knowledge embedding *** this framework,we examine current research to demonstrate how various forms of knowledge can be integrated into the ML pipeline and provide roadmap to specific ***,we present several case studies that illustrate specific implementations of KDML in the PHM domain,including inductive experience,physical model,and signal *** analyze the improvements in generalization capability and interpretability that KDML can ***,we discuss the challenges,potential applications,and usage recommendations of KDML in PHM,with a particular focus on the critical need for interpretability to ensure trustworthy deployment of artificial intelligence in PHM.
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