2019 Sixth Indian Control Conference (ICC)最新文献_第3页

Right of Way Rules based Collision Avoidance Approach Using Model Predictive Control 基于路权规则的模型预测控制避碰方法

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123203

Yogesh Kumar, Amith Manoharan, P. Sujit

引用次数: 1

An Incremental Algorithm for Estimating Extreme Quantiles 一种估计极端分位数的增量算法

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123207

A. Joseph, S. Bhatnagar

引用次数: 0

A Finite Time Adaptive Robust Regulation Control of Spacecraft under Limited Measurements 有限测量条件下航天器的有限时间自适应鲁棒调节控制

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123215

Syed Muhammad Amrr, Arunava Banerjee, M. Nabi

引用次数: 1

A Simplified SDRE Technique for Finite Horizon Tracking Problem in Optimal Control Systems 最优控制系统有限水平跟踪问题的一种简化SDRE技术

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123230

D. Naidu, Sudipta Paul, Ahmed Khamis, Craig Rieger

{"title":"A Simplified SDRE Technique for Finite Horizon Tracking Problem in Optimal Control Systems","authors":"D. Naidu, Sudipta Paul, Ahmed Khamis, Craig Rieger","doi":"10.1109/ICC47138.2019.9123230","DOIUrl":"https://doi.org/10.1109/ICC47138.2019.9123230","url":null,"abstract":"Closed loop optimal control of nonlinear systems using state dependent Riccati equation (SDRE) technique has been an active research area during the last decade. The existing SDRE technique for continuous time, finite horizon, optimal tracking problem is approximate and involves several steps which makes it computationally complex. In this paper, a simplified SDRE technique is proposed for a nonlinear closed loop finite horizon optimal tracking problem. For tracking, one is faced with not only solving the nonlinear matrix differential Riccati equation (DRE) but also solving the nonhomogeneous vector differential equation (VDE). The proposed simplified SDRE method for optimal tracking, without the assumption of the Riccati coefficient and vector coefficient being constant during the small intervals of the finite-horizon period, employs the analytic solution of matrix DRE and VDE and the associated MATLAB program developed by the authors of this paper at each small intervals, thereby avoiding the approximate nature and eliminating the several steps associated with the existing SDRE technique. The proposed simplified finite horizon SDRE tracking technique is illustrated with a permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS).","PeriodicalId":231050,"journal":{"name":"2019 Sixth Indian Control Conference (ICC)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122686690","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

Control of an Omnidirectional Mobile Base with Multiple Spherical Robots 多球面机器人全向移动基地的控制

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123198

V. Kadam, L. Vachhani, Abhishek Gupta

引用次数: 1

On Convergence of Pigeon Inspired Optimization Algorithm 鸽子启发优化算法的收敛性研究

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123217

Gangireddy Sushnigdha, Aeidapu Mahesh

引用次数: 0

Robust Wind Farm Layout Optimization under Uncertainty 不确定条件下稳健风电场布局优化

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123240

P. Mittal, K. Mitra

{"title":"Robust Wind Farm Layout Optimization under Uncertainty","authors":"P. Mittal, K. Mitra","doi":"10.1109/ICC47138.2019.9123240","DOIUrl":"https://doi.org/10.1109/ICC47138.2019.9123240","url":null,"abstract":"Wind energy turns out to be the most influential alternative source of energy to deal with the demand-supply and environmental crisis of fossil fuels. However, the very uncertain nature of wind is generally ignored while designing a wind farm. Depending on the decently long life span of wind turbines, wind farms can face long term variations in the wind flow, affecting the power production capability severely. In this study, a flexible robust optimization methodology has been proposed to design wind farm layouts under varying wind state conditions. The proposed methodology assumes different realizations of wind state uncertainty distributions in terms of different frequencies of occurrences for wind speeds and directions and provides solutions for the worst case and the best case scenarios by solving two-stage robust counterpart formulations. Using the idea of index representation of grids, a novel technique utilizing the concept of variable resolution grid on need has been proposed to provide Pareto solutions for the multi-objective cost-power trade-off problem. The pros and cons of these competitive solutions and the benefits of adopting the worst case over the deterministic solutions (for each scenario considering no uncertainty) have been thoroughly analyzed to provide an idea of the minimum guaranteed power production that can be achieved under uncertainty.","PeriodicalId":231050,"journal":{"name":"2019 Sixth Indian Control Conference (ICC)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131368042","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: 1

Fault tolerant pseudo-decentralized eMPC for energy efficiency in a multi-zone building 多区建筑能源效率的容错伪分散eMPC

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123173

A. Mona Subramaniam, Tushar Jain, J. Yamé

{"title":"Fault tolerant pseudo-decentralized eMPC for energy efficiency in a multi-zone building","authors":"A. Mona Subramaniam, Tushar Jain, J. Yamé","doi":"10.1109/ICC47138.2019.9123173","DOIUrl":"https://doi.org/10.1109/ICC47138.2019.9123173","url":null,"abstract":"This paper presents a novel integrated pseudo-decentralized fault-diagnosis and fault-tolerant approach based on the pseudo-decentralized economic model predictive control (pDeMPC) strategy for an HVAC system in a multi-zone building. Feedback linearization is employed to cancel out the bilinear and Hammerstein terms, thereby, resulting in an easily handleable linear system. A full order state-observer is designed to estimate the unmeasured wall temperatures of the zone because shared walls are the primary source of coupling between the interconnected zones. With this complete state information, the system is decomposed into control-oriented thermal models of individual zones. Subsequently, an integrated pseudo-decentralized fault-diagnosis and fault-tolerant approach based on pDeMPC scheme which utilizes the interaction among the zones is designed which can be easily scaled to buildings with a large number of zones, thereby, making it suitable for real-time implementation. SIMulation of Building and Devices (SIMBAD) toolbox is used for demonstrating the effectiveness of control and monitoring approach on a one floor, three-zone building.","PeriodicalId":231050,"journal":{"name":"2019 Sixth Indian Control Conference (ICC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125445998","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

Comparative Study of Optimal Long Short Term Memory Networks for One Day Ahead Solar Irradiance Hourly Forecast 未来一天太阳辐照度逐时预报的最佳长短期记忆网络比较研究

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123157

S. Miriyala, Sree Harsha Nagalla, K. Mitra

{"title":"Comparative Study of Optimal Long Short Term Memory Networks for One Day Ahead Solar Irradiance Hourly Forecast","authors":"S. Miriyala, Sree Harsha Nagalla, K. Mitra","doi":"10.1109/ICC47138.2019.9123157","DOIUrl":"https://doi.org/10.1109/ICC47138.2019.9123157","url":null,"abstract":"Energy sustenance is one of the key challenges India is facing in the contemporary time. Rise in global warming and the increasing need for dependency on clean energy has motivated researchers to develop novel techniques for harnessing maximum energy from renewable sources such as solar irradiance. However, one major issue which is impeding the large scale optimal implementation of solar farms is the uncertainty associated with solar irradiance. Although several statistical forecasting methods have helped in this regard, they could not contribute to efficient utilization of solar energy. In this work, long short term memory networks (LSTMs) are implemented for modelling the time series data of solar irradiance. LSTMs are deep neural networks which are proven to be extremely efficient in modelling nonlinear time series data with long term dependencies. However, LSTM networks are modelled using several heuristically governed parameters, making them an ineffective tool for time series regression. A novel multi-objective evolutionary optimization framework is proposed for optimal design of LSTM networks for emulating the real world solar irradiance data. The optimally trained LSTMs are used to forecast 1 day-ahead hourly prediction. LSTMs are compared with state-of-the-art system identification tools – Wavelet networks and feedforward neural networks through nonlinear auto-regressive exogenous modelling. LSTMs were found to be better with a root mean square error of 13% and R2 (correlation coefficient-a statistical measure of goodness of fit) value of 0.976.","PeriodicalId":231050,"journal":{"name":"2019 Sixth Indian Control Conference (ICC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130666924","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

Generalized Inverse-Free Kalman filter using Approximate Inverse of Block Diagonally Dominant Matrices 基于块对角占优矩阵近似逆的广义无逆卡尔曼滤波

2019 Sixth Indian Control Conference (ICC) Pub Date : 2019-12-01 DOI: 10.1109/ICC47138.2019.9123206

K. Babu, K. Detroja

{"title":"Generalized Inverse-Free Kalman filter using Approximate Inverse of Block Diagonally Dominant Matrices","authors":"K. Babu, K. Detroja","doi":"10.1109/ICC47138.2019.9123206","DOIUrl":"https://doi.org/10.1109/ICC47138.2019.9123206","url":null,"abstract":"To reduce the computational complexity of the Kalman filter an inverse free Kalman filter (IFKF) was proposed recently in [1]. The IFKF is a trade-off between complexity and accuracy. Motivated by the observation that the innovation covariance matrix structure largely depends on the structure of the observation matrix, in this manuscript, we propose a generalized inverse-free Kalman filter (GIFKF). The proposed GIFKF is a generalization of the IFKF to cases where there are redundant measurements or measurements with strong correlations. Though not encountered often, the case of redundant measurements still has a considerable number of applications. In such cases, we note that the assumption of diagonal dominance on the innovation covariance matrix may no longer be reasonable and could result in poor performance of IFKF. The GIFKF proposed in this paper alleviates this problem by replacing the diagonal dominance assumption with block diagonal dominance, which improves the accuracy and applicability compared to the IFKF. The accuracy of the proposed method and the conformity of the assumption of block diagonal dominance in the case of redundant measurements is established through simulation results.","PeriodicalId":231050,"journal":{"name":"2019 Sixth Indian Control Conference (ICC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131512525","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: 1