Hybrid Petri nets modeling for farm work flow

Guan, Senlin; Nakamura, Morikazu; Shikanai, Takeshi; Okazaki, Takeo

doi:10.1016/j.compag.2007.12.006

Cited by 44 publications

(15 citation statements)

References 19 publications

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“…Another implementation of a wellknown method from other scientific areas is Petri nets. Guana et al (2008) introduced hybrid Petri nets into their modeling of farm workflow. This was because agricultural operations involve both continuous and discrete events, and hybrid Petri nets conventionally comprise a continuous part and a discrete part.…”

Section: Online Fleet Managementmentioning

confidence: 99%

Emerging Footprint Technologies in Agriculture, from Field to Farm Gate

Fountas

Bartzanas

Bochtis

2011

Intelligent Agrifood Chains and Networks

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During the last few years, the agricultural sector has been through a critical phase, having been seriously affected by several factors. At an international level the agreements of the International Trade Organization and at a European level the new Common Agricultural Policy have resulted in problems with the competitiveness of agricultural products and the necessity for improvements in production methods of safe, healthy, high-quality products that are also in accordance with the objective of environmental protection.The agricultural sector is currently benefiting from a wide range of new information and communication technology (ICT) tools that are helping improve the flow of information in the real-time management of agricultural crops. New technologies to enhance the precision and automation of crop management are continuously being developed, tested and evaluated. The tools of precision agriculture and other information technologies should move into mainstream agricultural management when they are sufficiently developed and incorporated into the production chain. These technologies are paving the way for the reversal of the current trend towards heavy-machinery systems, replacing them with teams of smaller field robots. In this view of the future, fleet management will maintain its key role in maximizing overall efficiency, which it will achieve by optimizing the selection, dispatching and in-field coordination of these teams. This chapter describes advanced technologies and methods that can provide an efficient integrated in-field production system that will meet the objectives of product quality, resource usage, economic feasibility and environmental impact. Chapter sections include precision agriculture, field robotics, radio frequency identification (RFID) technology, automated data recording and fleet management. PRECISION AGRICULTUREPrecision agriculture (PA) can be defined as the management of spatial and temporal variability to improve economic returns and reduce environmental impact. This can be achieved through using appropriate technologies within a coherent management structure. The technology provides the tools and management decides how the tools should be used. PA uses these new technologies to reduce the unit area of treatment from, in some cases, the farm down to field or even sub-field level.Intelligent Agrifood Chains and Networks, First Edition. Edited by Michael Bourlakis, Ilias Vlachos and Vasileios Zeimpekis.

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Section: Online Fleet Managementmentioning

confidence: 99%

Emerging Footprint Technologies in Agriculture, from Field to Farm Gate

Fountas

Bartzanas

Bochtis

2011

Intelligent Agrifood Chains and Networks

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“…HPN is an extension of petri net (PN), which is suitable for graphical representation. Recently, HPN has been used in various fields [6][7][8], but there are no works for continuous processing lines. HPN helps the designer to intuitively grasp the behavior of the plant since each component of the line directly corresponds to that of the HPN, such as places and transitions.…”

Section: Introductionmentioning

confidence: 99%

Model predictive control for line pacing in steel processing

Konaka

Suzuki

Asano

et al. 2012

IEEJ Transactions Elec Engng

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Line pacing control in steel processing lines is known to be a difficult task for operators.?They usually take a conservative control policy in order to avoid shutdown, and the processing capacity of the line has not been fully utilized yet. This paper presents a new modeling and control technique for line pacing based on a hybrid petri net (HPN) and mixed logical dynamical system (MLDS) expressions. The proposed modeling method can harmoniously integrate continuous and discrete aspects of the system. Moreover, the proposed method can provide a suitable formulation for numerical optimization. Based on this hybrid system modeling, the closed-loop control can be realized by the receding horizon scheme. Numerical examples demonstrate that the processing capacity can be fully utilized by the proposed method.

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“…The farm work scheduling comprises a model for modeling the farm works and a scheduling system for optimizing the farm work schedule. The model, which is a hybrid Petri nets first introduced into agricultural production (Guan et al, 2008), graphically formulates the farm work flow and simulates the overall status of the progress of farm work and the state of resources. The scheduling system performs the resource assignment and the computation for a long-term schedule (Guan et al, 2009).…”

Section: Introductionmentioning

confidence: 99%