53rd IEEE Conference on Decision and Control最新文献_第9页

Controlling flutter for nonlinear panels in subsonic flows via structural velocity feedback 利用结构速度反馈控制非线性板在亚音速流动中的颤振

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7039443

I. Lasiecka, J. Webster

{"title":"Controlling flutter for nonlinear panels in subsonic flows via structural velocity feedback","authors":"I. Lasiecka, J. Webster","doi":"10.1109/CDC.2014.7039443","DOIUrl":"https://doi.org/10.1109/CDC.2014.7039443","url":null,"abstract":"Mechanical control of flutter for a thin panel immersed in an inviscid flow is considered. The model arises in aeroelasticity and comprises the interaction between a clamped von Karman plate a surrounding potential flow of gas. Recent results show that the plate dynamics of the model converge to a global compact attracting set of finite dimension [6]. This result was obtained in the absence of mechanical damping of any type. Here, we incorporate a sufficiently large velocity feedback control applied to the structure to show that the full flow-plate system exhibits strong convergence to a stationary state (when flows are subsonic and a “good” energy identity is available). Our method is based on first showing the desired convergence properties when the plate dynamics exhibit additional regularity. We then show a dichotomy for the plate dynamics: they are either asymptotically regular or the plate velocities decay uniformly exponentially. In the case when no additional plate regularity is available, we utilize an approximation by smooth initial data; this requires propagation of initial regularity on the infinite time horizon. The final result complements results previous obtained (for this model and similar models), as we show that there is a strong convergence for the entire dynamics and that the limiting behavior of the flow-plate system is, in fact, stationary. Physically, this implies that flutter (a non-static end behavior) can be eliminated by a velocity feedback control in subsonic flows.","PeriodicalId":202708,"journal":{"name":"53rd IEEE Conference on Decision and Control","volume":"27 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120921139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On observer design for a class of continuous-time affine switched or switching systems 一类连续仿射切换系统的观测器设计

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7040366

L. Menini, C. Possieri, A. Tornambè

引用次数: 15

Minimum switching limit cycle oscillations for systems of coupled double integrators 耦合双积分器系统的最小开关极限环振荡

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7040114

A. Garulli, Antonio Giannitrapani, Mirko Leomanni

引用次数: 8

Binary consensus through binary communication 通过二进制通信实现二进制共识

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7039467

Jemin George, A. Swami

引用次数: 6

Structured covariance estimation for state prediction 状态预测的结构协方差估计

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7039397

Weichang Li, T. A. Badgwell

{"title":"Structured covariance estimation for state prediction","authors":"Weichang Li, T. A. Badgwell","doi":"10.1109/CDC.2014.7039397","DOIUrl":"https://doi.org/10.1109/CDC.2014.7039397","url":null,"abstract":"In this paper we propose a structurally constrained expectation-maximization (EM) algorithm for estimating noise covariances in state-space models, for the purpose of state prediction and control. More specifically, we generalize the problem of covariance estimation on the basis of given i.i.d sample sequence to the dynamic setting where the samples (i.e. state and observation noises) are observed only through the measurement data, or equivalently, drawn from the conditional distribution governed by the dynamic model. By applying the expectation maximization (EM) algorithm to the innovation model representation, we view the resulting ML covariance estimates as the conditional sample covariances, and augment the negative log-likelihood function with matrix norm penalty terms that enforce low-rank and low cardinality structure in the estimated covariances or their inverses. These constraints serve to reflect realistic problem structure expected from model knowledge, yet are still general and flexible enough to be broadly applicable. In addition, the new derivation of the EM algorithm based on the innovation representation gives the common sufficient statistic for both the process and observation noise covariances. This illustrates the coupling between the two covariance estimates, and in simulated cases, enables the calculation of an upper performance bound against which the EM estimates can be compared. The use of the innovation representation also provides a tractable connection to the existing techniques such as the Autocovariance Least Squares (ALS) algorithm. Numerical results comparing the constrained EM and the ALS algorithms are also provided, showing favorable performance for the EM covariance estimates.","PeriodicalId":202708,"journal":{"name":"53rd IEEE Conference on Decision and Control","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121694415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Discounting the past in robust finite-state systems 在鲁棒有限状态系统中贴现过去

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7039486

M. Rungger, P. Tabuada

引用次数: 0

Control allocation based fault-tolerant control design for spacecraft attitude tracking 基于控制分配的航天器姿态跟踪容错控制设计

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7040167

Qiang Shen, Danwei W. Wang, Senqiang Zhu, E. Poh

引用次数: 7

Stability analysis for replicator dynamics of evolutionary snowdrift games 进化雪堆博弈复制因子动力学的稳定性分析

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7040094

Pouria Ramazi, M. Cao

引用次数: 12

A model-based approach for prediction-based interconnection of dynamic systems 基于模型的动态系统预测互连方法

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7039897

G. Stettinger, M. Horn, M. Benedikt, J. Zehetner

引用次数: 19

Event-triggered output feedback stabilization of networked systems with external disturbance 具有外部干扰的网络系统的事件触发输出反馈镇定

53rd IEEE Conference on Decision and Control Pub Date : 2014-12-01 DOI: 10.1109/CDC.2014.7039943

Eloy García, P. Antsaklis

引用次数: 13