Collaborative Control Protocol for Agricultural Cyber-Physical System

被引:14
作者
Dusadeerungsikul, Puwadol Oak [1 ,2 ]
Nof, Shimon Y. [1 ,2 ]
Bechar, Avital [3 ]
Tao, Yang [4 ]
机构
[1] Purdue Univ, PRISM Ctr, 315 Grant St, W Lafayette, IN 47907 USA
[2] Purdue Univ, Sch Ind Engn, 315 Grant St, W Lafayette, IN 47907 USA
[3] Agr Res Org, Inst Agr Engn, Volcani Ctr,POB 6, IL-50250 Bet Dagan, Israel
[4] Univ Maryland, Fischell Dept Bioengn, Bio Imaging & Machine Vis Lab, College Pk, MD 20742 USA
来源
25TH INTERNATIONAL CONFERENCE ON PRODUCTION RESEARCH MANUFACTURING INNOVATION: CYBER PHYSICAL MANUFACTURING | 2019年 / 39卷
关键词
Agricultural Robotic System; Collaborative Agents; Collaborative Control Theory; Greenhouse; Precision Agriculture;
D O I
10.1016/j.promfg.2020.01.330
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this article, a Collaborative Control Protocol for Robotic and Cyber-Physical System (CCP-CPS) is presented. CCP-CPS, which enables an application of robotics in a CPS system for smart and precision agriculture (PA), aims to monitor and identify stresses in greenhouse crops by a hyperspectral analysis method. Roles of CCP-CPS are to assign tasks to agents, identify and resolve conflicts and errors in the system, and enable a more effective collaboration and interaction among agents in CPS, compared to traditional non-collaborative and non-CPS approach. Collaborative Control Theory (CCT) is utilized for two system levels; protocol and agent level (CCP level), and CPS and environment level (CPS level). We use two case studies to test and validate our method with alternative approaches. The results from computer simulation show that 1) CCP-CPS can identify the highest number of greenhouse locations containing stresses, 2) CCP-CPS can utilize available resources (time) effectively, and 3) CCP-CPS can respond to an emergency stress situation faster and have more tolerance capability with system conflicts and errors, by having human integration and cyber-augmented greenhouse system, than other monitoring systems. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:235 / 242
页数:8
相关论文
共 12 条
[1]   A review and framework of laser-based collaboration support [J].
Bechar, A. ;
Nof, S. Y. ;
Wachs, J. P. .
ANNUAL REVIEWS IN CONTROL, 2015, 39 :30-45
[2]   Agricultural robots for field operations: Concepts and components [J].
Bechar, Avital ;
Vigneault, Clement .
BIOSYSTEMS ENGINEERING, 2016, 149 :94-111
[3]  
Dusadeerungsikul PO., 2019, COLLABORATIVE CONTRO
[4]  
Edan Y, 2009, SPRINGER HANDBOOK OF AUTOMATION, P1095, DOI 10.1007/978-3-540-78831-7_63
[5]   Agricultural cyber physical system collaboration for greenhouse stress management [J].
Guo, Ping ;
Dusadeeringsikul, Puwadol ;
Nof, Shimon Y. .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2018, 150 :439-454
[6]   Design and application of task administration protocols for collaborative production and service systems [J].
Ko, Hoo Sang ;
Nof, Shimon Y. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2012, 135 (01) :177-189
[7]   Combined demand and capacity sharing with best matching decisions in enterprise collaboration [J].
Moghaddam, Mohsen ;
Nof, Shimon Y. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2014, 148 :93-109
[8]   Collaborative control theory for e-Work, e-Production, and e-Service [J].
Nof, S. Y. .
ANNUAL REVIEWS IN CONTROL, 2007, 31 (02) :281-292
[9]  
Nof S.Y., 2015, BARD WORKSHOP
[10]  
Sethi S, 2021, J AM SOC NEPHROL, V32, P463, DOI [10.1080/18824889.2021.1893936, 10.1016/j.ijar.2020.06.001, 10.1038/s41598-022-19167-8]