2019 Fifth Indian Control Conference (ICC)最新文献_第2页

Cooperative Relative Pose Estimation to Aid Landing of an Unmanned Aerial Vehicle on a Moving Platform 辅助无人机在移动平台上着陆的协同相对姿态估计

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715633

Nikita Mishra, Anusna Chakraborty, Rajnikant Sharma, K. Brink

引用次数: 4

Input/output-to-state stability of discrete-time switched nonlinear systems under restricted switching 受限切换下离散时间切换非线性系统的输入/输出-状态稳定性

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715560

A. Kundu

引用次数: 7

GNSS-based spacecraft navigation in elliptical and High Earth Orbits using Single Propagation Unscented Kalman Filters 基于单传播无嗅卡尔曼滤波器的椭圆轨道和高轨道gnss航天器导航

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715595

Sanat K. Biswas, A. Dempster

引用次数: 1

Neural-Linear Architectures for Sequential Decision Making 序列决策的神经线性体系结构

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715603

Tom Zahavy, Matan Haroush, Nadav Merlis, D. Mankowitz, Shie Mannor

{"title":"Neural-Linear Architectures for Sequential Decision Making","authors":"Tom Zahavy, Matan Haroush, Nadav Merlis, D. Mankowitz, Shie Mannor","doi":"10.1109/INDIANCC.2019.8715603","DOIUrl":"https://doi.org/10.1109/INDIANCC.2019.8715603","url":null,"abstract":"Making optimal decisions, while learning in dynamic environments like Markov Decision Processes and Multi-armed Bandits, often requires the computation of accurate uncertainty estimates. However, learning directly from raw, high dimensional inputs like vision and natural language, is typically done using deep neural networks, for which such accurate estimates are not available. Neural-linear algorithms address this challenge by utilizing linear algorithms (for which accurate uncertainty estimates exist) on top of a non-linear (deep) representation that is learned directly from the raw input. Such architectures have been recently explored, showing superior performance compared to both deep and linear state-of-the-art algorithms. A practical challenge in this approach is that the representation is assumed to be fixed over time when used by the linear algorithm, while the deep learning based representation changes as the optimization proceeds. In this talk, I will review recent neural-linear algorithms and discuss an algorithmic approach to deal with representations that change over time. In particular, I will present a linear fitted Q iteration algorithm that refines the weights of the last layer of a deep q network and improves its performance in the arcade learning environment, a neural-linear Thompson Sampling algorithm for contextual bandits and deep reinforcement learning, and an action elimination algorithm for text-based games that eliminates actions based on a linear upper confidence bound.","PeriodicalId":396409,"journal":{"name":"2019 Fifth Indian Control Conference (ICC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128006474","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

Development of a Generic Flight Controller for a High Performance Fixed Wing Aircraft 高性能固定翼飞机通用飞行控制器的研制

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715590

P. Lathasree, A. Pashilkar, N. Sundararajan

引用次数: 0

Molecular Weight Control in Semi Batch Copolymerization Reactor through Temperature Tracking: Evaluation of Control Strategies 基于温度跟踪的半间歇共聚反应器分子量控制:控制策略的评价

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715596

K. Silpa, R. Kamesh, K. Yamuna Rani

{"title":"Molecular Weight Control in Semi Batch Copolymerization Reactor through Temperature Tracking: Evaluation of Control Strategies","authors":"K. Silpa, R. Kamesh, K. Yamuna Rani","doi":"10.1109/INDIANCC.2019.8715596","DOIUrl":"https://doi.org/10.1109/INDIANCC.2019.8715596","url":null,"abstract":"Molecular weight is one of the influential attributes in a polymerization process and its control in semi-batch operation poses considerable difficulty due to complexities of the process. The present study focuses on the development of different control strategies for controlling the molecular weight by tracking reactor temperature and composition control using jacket temperature and feed flow rate as manipulated variables. The copolymerization of styrene acrylonitrile with xylene as solvent and AIBN as initiator is considered for the present study. The control strategies evaluated are Multi-loop-proportional integral (PI) control, multivariable-PI control and nonlinear generic model control (GMC). The present study showed that control of temperature and composition has resulted in achieving the desired molecular weight. Nonlinear GMC control is able achieve targeted molecular weight closely even in the presence of unmeasured load disturbances in the monomer feed concentration and initial initiator concentration, whereas multi-loop and multivariable PI controllers resulted in some offset.","PeriodicalId":396409,"journal":{"name":"2019 Fifth Indian Control Conference (ICC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115813075","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

Analysis and Application of Linear ADRC for the Control of DC-DC Converters 线性自抗扰控制器在DC-DC变换器控制中的分析与应用

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715625

Soumyadeep Bose, Y. V. Hote, V. Siddhartha

引用次数: 9

A Switched Adaptive Observer Design Without Persistence Of Excitation 无持续激励的切换自适应观测器设计

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715558

Atul Katiyar, S. Roy, S. Bhasin

引用次数: 2

Simultaneous Resource Allocation and Route Optimization in Dynamic Multi-Agent Networks 动态多智能体网络中的同步资源分配与路由优化

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715605

Amber Srivastava, S. Salapaka

{"title":"Simultaneous Resource Allocation and Route Optimization in Dynamic Multi-Agent Networks","authors":"Amber Srivastava, S. Salapaka","doi":"10.1109/INDIANCC.2019.8715605","DOIUrl":"https://doi.org/10.1109/INDIANCC.2019.8715605","url":null,"abstract":"The objective of simultaneous resource allocation and route optimization problem is to overlay a network of communication resources on an existing network of sensors (or sites); to facilitate the flow of information packets, originating at each sensor, to a destination center (or central processing unit) such that the total cost of communication is minimized. This is an NP-hard problem and the associated cost function is riddled with multiple poor local minima even for fixed locations of sensors and destination center. In the case when the sensors and the destination center have associated dynamics, determining resource location and routing dynamics adds significantly to the complexity. Here we propose a framework that uses the Maximum-Entropy-Principle and a smooth approximation to the total communication cost as a Lyapunov function, to solve the simultaneous resource allocation and route optimization problem in a dynamic setting. Simulation results demonstrate that the proposed algorithm outperforms the frame-by-frame approach with regards to the practical feasibility of the resource dynamics apart from saving heavily on the computational expense involved in the latter.","PeriodicalId":396409,"journal":{"name":"2019 Fifth Indian Control Conference (ICC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130246014","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

Reachability based Model Predictive Control for Semi-active Suspension System 基于可达性的半主动悬架系统模型预测控制

2019 Fifth Indian Control Conference (ICC) Pub Date : 2019-01-01 DOI: 10.1109/INDIANCC.2019.8715601

Karthik Murali Madhavan Rathai, O. Sename, M. Alamir

{"title":"Reachability based Model Predictive Control for Semi-active Suspension System","authors":"Karthik Murali Madhavan Rathai, O. Sename, M. Alamir","doi":"10.1109/INDIANCC.2019.8715601","DOIUrl":"https://doi.org/10.1109/INDIANCC.2019.8715601","url":null,"abstract":"This paper proposes a Model Predictive Control (MPC) framework for control of a quarter car semi-active suspension system based on reachable sets approach. The proposed approach provides the flexibility of systematically including the information on the bounds of future road disturbances over the prediction horizon onto the MPC problem formulation by means of reachable sets. This inclusion of future bounds into control design leverages the efficiency of the operation of suspension system. Firstly, a unique Linear Parameter Varying (LPV) model is formulated for control design, which implicitly accounts for the dissipativity constraint of semi-active suspension system. Secondly, an efficient online computation of the reachable sets with the available disturbance information at the current instant for the MPC problem is developed. The proposed methodology is an integration of the preceding steps into a single MPC problem. The effectiveness of the proposed methodology is validated through simulations and the results exhibit better performance of the proposed controller compared to skyhook controller in terms of satisfaction of objective and constraint requirements.","PeriodicalId":396409,"journal":{"name":"2019 Fifth Indian Control Conference (ICC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131160202","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: 9