Planning plant operating procedures for chemical plant

Aylett, Ruth; Soutter, James; Petley, Gary; Chung, Pei-Jung; Edwards, Derek

doi:10.1016/s0952-1976(01)00012-4

Cited by 10 publications

(5 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many realistic contexts in which planning can be applied feature a mixture of discrete and continuous behaviours. For example, the management of a refinery (Boddy & Johnson, 2004), the start-up procedure of a chemical plant (Aylett, Soutter, Petley, Chung, & Edwards, 2001), the control of an autonomous vehicle (Léauté & Williams, 2005) and the coordination of the activities of a planetary lander (Blake et al, 2004) are problems for which reasoning about continuous change is fundamental to the planning process. These problems also contain discrete change which can be modelled through traditional planning formalisms.…”

Section: Motivationmentioning

confidence: 99%

Modelling Mixed Discrete-Continuous Domains for Planning

Fox¹,

Long²

2006

jair

164

184

View full text Add to dashboard Cite

In this paper we present pddl+, a planning domain description language for modelling mixed discrete-continuous planning domains. We describe the syntax and modelling style of pddl+, showing that the language makes convenient the modelling of complex timedependent effects. We provide a formal semantics for pddl+ by mapping planning instances into constructs of hybrid automata. Using the syntax of HAs as our semantic model we construct a semantic mapping to labelled transition systems to complete the formal interpretation of pddl+ planning instances.An advantage of building a mapping from pddl+ to HA theory is that it forms a bridge between the Planning and Real Time Systems research communities. One consequence is that we can expect to make use of some of the theoretical properties of HAs. For example, for a restricted class of HAs the Reachability problem (which is equivalent to Plan Existence) is decidable.pddl+ provides an alternative to the continuous durative action model of pddl2.1, adding a more flexible and robust model of time-dependent behaviour.

show abstract

Section: Motivationmentioning

confidence: 99%

Modelling Mixed Discrete-Continuous Domains for Planning

Fox¹,

Long²

2006

jair

164

184

View full text Add to dashboard Cite

show abstract

“…Furthermore, a new area of study called process planning has emerged from the application of automated planning techniques to machining procedures ( [13], [14], [15]). There are many representations for a control program for a manufacturing system like, for example, GRAFCET, Ladder or Petri nets.…”

Section: Discussionmentioning

confidence: 99%

Self-Reconfigurable Control - Part I: Modeling Based on Automated Planning

2015

Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

View full text Add to dashboard Cite

Abstract-This paper presents a new formal modeling framework for reconfigurable control. The main idea is to use the STRIPS (STanford Research Institute Problem Solver), a formal language for automated planning which can integrate the cause-effect knowledge and the automated reasoning mechanism into one model. A qualitative model based on a graph of states is chosen. Transitions between states are determined from the possible actions (as defined as controls to the actuators). Each action is modeled in terms of preconditions and effects. The STRIPS can qualitatively define the fault models without requiring detail and precise knowledge of faulty components. Automated planning is an interesting tool for reconfigurable control. Since the process may end up in any one of a very large number of states after a break-down, it is not realistic to have recovery plans designed in advance for all such states. It is, thus, desirable to invoke a planner in the case of break-downs, which finds a plan that brings the process back into normal operation again, and that is the nature of reconfigurable control.

show abstract

“…To define the link between the evolutions of resources and the product flow, the product flow and resource evolutions are modeled in the same operation. The operation structuring is based on the model proposed in automated planning field (Sandewall & Ronnquist, 1986) (Ghallab et al, 2004) and used by (Klein, 1999), (Castillo et al, 2000), (Aylett, 2001) in the manufacturing and batch-process field.…”

Section: Constraint Levels Satisfied By a Control Lawmentioning

confidence: 99%

Logic control law design for automated manufacturing systems

Henry

Zamaï

Jacomino

2012

Engineering Applications of Artificial Intelligence

View full text Add to dashboard Cite

To cite this version:Henry Sébastien, Éric Zamaï, Mireille Jacomino. Logic control law design for automated manufacturing systems. Engineering Applications of Artificial Intelligence, Elsevier, 2012, 25 (4) AbstractTo respond rapidly to the highly volatile market, the reconfigurable manufacturing systems (RMS) have brought forward challenging issues. First of all there is a need to build a formal model of a manufacturing configuration. Second it has to be rather easy to derive the models associated to the manufacturing configuration changes (Reconfiguration) from such an initial model. An off-line method of rapid design of an optimal logic control law (configuration) based on Petri net (PN) is presented in this paper. From a controlled system modeling point of view, the main characteristics of the level 1 of the CIM architecture are depicted. Subsequently, the formal tool used in the Automated Planning field is extended to provide a controlled system model. The concept of operation is structured in order to introduce the behavioral properties of the operations. A four-step method is then proposed to design a logic control law that satisfies several goals: reduction of the lead time, satisfaction of the work orders objectives, minimization of the time cycle. Finally, the proposed design method is illustrated on a manufacturing cell.

show abstract

Planning plant operating procedures for chemical plant

Cited by 10 publications

References 18 publications

Modelling Mixed Discrete-Continuous Domains for Planning

Modelling Mixed Discrete-Continuous Domains for Planning

Self-Reconfigurable Control - Part I: Modeling Based on Automated Planning

Logic control law design for automated manufacturing systems

Contact Info

Product

Resources

About