2017 American Control Conference (ACC)最新文献_第5页

Life prediction model for grid-connected Li-ion battery energy storage system 并网锂离子电池储能系统寿命预测模型

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963578

K. Smith, Aron Saxon, M. Keyser, B. Lundstrom, Ziwei Cao, A. Roc

引用次数: 125

Integrated ACC and CACC development for Heavy-Duty Truck partial automation 重型卡车部分自动化的集成ACC和CACC开发

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963720

Xiao-Yun Lu, S. Shladover

引用次数: 33

Deep reinforcement learning for partial differential equation control 偏微分方程控制的深度强化学习

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963427

Amir-massoud Farahmand, S. Nabi, D. Nikovski

引用次数: 34

Handling multi-rate and missing data in system identification 处理系统识别中的多速率和缺失数据

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963057

Mudassir M. Rashid, P. Mhaskar, C. Swartz

引用次数: 0

Linear quadratic control for sampled-data systems with stochastic delays 随机时滞采样数据系统的线性二次控制

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963242

M. Wakaiki, Masaki Ogura, J. Hespanha

引用次数: 2

ℒ1 adaptive anti-slug control 1自适应抗段塞流控制

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7962993

S. J. Ohrem, C. Holden, E. Jahanshahi, S. Skogestad

引用次数: 1

Feedback tracking control schemes for a class of underactuated vehicles in SE(3) 一类欠驱动车辆的反馈跟踪控制方案

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963067

Rakesh R. Warier, A. Sanyal, Srikant Sukumar, V. S. Prabhakaran

{"title":"Feedback tracking control schemes for a class of underactuated vehicles in SE(3)","authors":"Rakesh R. Warier, A. Sanyal, Srikant Sukumar, V. S. Prabhakaran","doi":"10.23919/ACC.2017.7963067","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963067","url":null,"abstract":"A trajectory tracking control scheme for a class of underactuated vehicles is presented here. The underactuated vehicle is modeled as a rigid body to which control thrust is applied along a single body-fixed axis and control torque can be applied along all three body-fixed coordinate axes. The combined rotational and translational motion of the rigid body is underactuated with the degree of underactuation two. Such an actuation scheme is reflective of a wide range of vehicles such as vertical take-off and landing (VTOL) aircraft, fixed-wing aircraft, and quadcopter uncrewed aerial vehicles (UAVs). For this class of underactuated vehicles, the proposed controller gives exponential stabilization of the position tracking error. Additionally, the component of the angular velocity parallel to the thrust direction, is regulated to be zero under the proposed control scheme. The other two components of the angular velocity track desired profiles that lead to exponential stabilization of the desired position trajectory; this angular velocity tracking control scheme is finite time stable. The combination of these schemes leads to guaranteed exponential stability of the overall feedback control scheme. A set of numerical simulation results that illustrate the performance of the overall feedback tracking control scheme is provided.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129771108","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: 6

Hybrid solution of nonlinear stochastic optimal control problems using Legendre Pseudospectral and generalized Polynomial Chaos algorithms 用Legendre伪谱和广义多项式混沌算法混合求解非线性随机最优控制问题

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963351

F. Harmon

{"title":"Hybrid solution of nonlinear stochastic optimal control problems using Legendre Pseudospectral and generalized Polynomial Chaos algorithms","authors":"F. Harmon","doi":"10.23919/ACC.2017.7963351","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963351","url":null,"abstract":"A novel hybrid technique is discussed to numerically solve nonlinear stochastic optimal control (OC) problems with numerous potential applications. The hybrid technique combines a Legendre Pseudospectral Method (LPM) with a generalized Polynomial Chaos (gPC) method, which are highly accurate numerical methods for solving deterministic OC problems and stochastic differential equations (SDE), respectively. The hybrid algorithm first selects samples from the random space using collocation nodes, inserts those sample values into the differential equations of the OC problem, and then uses a pseudospectral-based deterministic solver to generate solutions for each of the resulting deterministic problems. The set of deterministic solutions (i.e., ensemble of random realizations) are then used to construct a polynomial representation of the solution to the stochastic OC problem as a function of the random inputs using a gPC method (i.e., a high-order stochastic collocation method). The hybrid technique is used to solve a nonlinear stochastic OC problem to demonstrate its utility. The algorithm is a highly accurate technique for solving nonlinear OC problems with uncertain parameters. The hybrid technique will allow the user to analyze the solution to an OC problem and understand how uncertainty on the parameters such as the states, initial conditions, and boundary conditions can affect the solution (i.e., uncertainty quantification). The algorithm may also be useful for near real-time OC since a new trajectory can be followed if the uncertainty can be estimated.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127168968","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: 3

A tutorial on control-oriented modeling and control of wind farms 面向控制的风电场建模和控制教程

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7962923

S. Boersma, B. Doekemeijer, P. Gebraad, P. Fleming, J. Annoni, A. Scholbrock, J. Frederik, J. Wingerden

{"title":"A tutorial on control-oriented modeling and control of wind farms","authors":"S. Boersma, B. Doekemeijer, P. Gebraad, P. Fleming, J. Annoni, A. Scholbrock, J. Frederik, J. Wingerden","doi":"10.23919/ACC.2017.7962923","DOIUrl":"https://doi.org/10.23919/ACC.2017.7962923","url":null,"abstract":"Wind turbines are often sited together in wind farms as it is economically advantageous. However, the wake inevitably created by every turbine will lead to a time-varying interaction between the individual turbines. Common practice in industry has been to control turbines individually and ignore this interaction while optimizing the power and loads of the individual turbines. However, turbines that are in a wake experience reduced wind speed and increased turbulence, leading to a reduced energy extraction and increased dynamic mechanical loads on the turbine, respectively. Neglecting the dynamic interaction between turbines in control will therefore lead to suboptimal behaviour of the total wind farm. Therefore, wind farm control has been receiving an increasing amount of attention over the past years, with the focus on increasing the total power production and reducing the dynamic loading on the turbines. In this paper, wind farm control-oriented modeling and control concepts are explained. In addition, recent developments and literature are discussed and categorized. This paper can serve as a source of background information and provides many references regarding control-oriented modeling and control of wind farms.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132209382","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: 163

Distributed and decentralized Kalman filtering for Cascaded Fractional order systems 级联分数阶系统的分布式和分散卡尔曼滤波

2017 American Control Conference (ACC) Pub Date : 2017-05-24 DOI: 10.23919/ACC.2017.7963766

Martin Kupper, Iñigo Sesar Gil, S. Hohmann

引用次数: 4