Modelling, control and animated simulation of complex process in robotised FMS

Abstract

fax: + (44 902) 322 680; phone:+(.)322 716 School of Chemical Engineering, CE Lab., University of Bradford Richmond Rd., Bradford BD7 lDP, UK, fax: +(44 274) 733 466; phone: +(44 422)83 1923 Abstract -A methodology of studying and designing scheduling control algorithms and Petri-net supervisor implementing them for robotised F M S has been developed. It is of analytic-simulation type, the analytic part using Petri-net modelling and the simulation part making using animation. It makes visually tangible the F M S processes and reveals inconsistency or error in the derived scheduling control algorithms. INTRODUCTION In spite of considerable theoretical advances in modelling and control of discrete-event dynamic systems PEDS) including the problem of stabilising compensator, e.g. queuing networks [l], Petri's networks [2]-[3], operational analysis [4], Ho's state analysis [5], real-world implementable solutions are sought through an iterative analytic-simulation

FMS intelligent supervision and control 2: Communications among machines under FPSC

“…The here presented novel or else innovated results are well grounded on the compatible usage of system-theoretic results for stochastic Petri-nets [12,19,25], finite-state machines [13,16], fuzzy-Petri-net reasoning emulator [15], and discrete-event simulation modelling [9,10,22] The innovated developments have been derived on the grounds of compatible use of stochastic Petri-net and automata in OOMrepresented models [3,8,[27][28][29] to describe discrete-event communications [22,25] between subsystems that are encompassed in a case study of a medium-size FMS [27]. These results have been validated only by simulation in so far.…”

“…Namely, these may be identified as follows: flexible automation [34] following the FMS concept (e.g. Figures 1 and 2); embedded intelligence [2,4,7,[35][36][37] in automation infrastructure and intelligent-agent based integrated control and supervision [12][13][14][15]; and discrete-event supervisory control organizer [29,30,15], in particular. The essential underlying problem in common, it should be noted, is the controlled communication between subsystems (Ashby, 1970;Dou and Peng;1992;Gielingh et al, 1991;Hoare, 1985;Holvoet, 1995;Huvenoit et al, 1995;Kosbar and Schneider, 1992;Planque et al,.…”

Enhancing Learning Experience With Dynamic Animation

“…In [2], a real time simulation/animation tool was developed to facilitate the evaluation of active suspension systems. In [3], animation of flexible manufacturing system was carried out in conjunction with modeling and control. Arrival of student versions of graphical simulation software such as Matlab, VisSim, and LabVIEW sparked interests in adding an animation stage to the simulation.…”