Model-based control synthesis of continuous-discrete systems

Chouikha, Mourad; Schnieder, Eckehard

doi:10.1109/icsmc.1999.812446

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…1) combines the hybrid dynamic model and the requirement specification in an algorithmic procedure to directly get a controller that establishes the desired properties of the plant. Examples for approaches that follow this path are published in (Asarin et al, 2000b, Chouikha and Schnieder, 1999, Gokbayrak and Cassandras, 2000, Moor et al, 2001a, Trontis and Spathopoulos, 2001. Some of these methods aim at computing all admissible control inputs that fulfill the requirements for specific scenarios.…”

Section: Discrete Controllers For Hybrid Dynamic Systemsmentioning

confidence: 99%

Modelling, Analysis, and Design of Hybrid Systems

Engell¹,

Frehse²,

Schnieder³

2002

Lecture Notes in Control and Information Sciences

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PrefaceIn 1995, the Deutsche Forschungsgemeinschaft (DFG), the largest public research funding organization in Germany, decided to launch a priority program (Schwerpunktprogramm in German) called Kondisk-Dynamics and Control of Systems with Mixed Continuous and Discrete Dynamics. Such a priority program is usually sponsored for six years and supports about twenty scientists at a time, in engineering and computer science mostly young researchers working for a doctoral degree. There is a yearly competition across all disciplines of arts and sciences for the funding of such programs, and the group of proposers was the happy winner of a slot in that year. The program started in 1996 after an open call for proposals; the successful projects were presented and re-evaluated periodically, and new projects could be submitted simultaneously. During the course of the focused research program, 25 different projects were funded in 19 participating university institutes, some of the projects were collaborative efforts of two groups with different backgrounds, mostly one from engineering and one from computer science.There were two main motivations for establishing Kondisk. The first was the fact that technical systems nowadays are composed of physical components with (mostly) continuous dynamics and computerized control systems where the reaction to discrete events plays a major role, implemented in Programmable Logic Controllers (PLCs), Distributed Control Systems (DCSs) or real-time computer systems. These two elements interact closely, and the resulting behavior can be surprisingly complex even for very simple systems, as demonstrated for the filling of three or more tanks by a switched server (Chase et al., 1993. Such complex behavior can neither be analyzed nor synthesized by methods that are based on either purely continuous or purely discrete systems theory. Despite the lack of theoretical tools or even powerful simulation environments for systems with mixed continuous and discrete dynamics, such systems have been engineered successfully on a trial-and-error basis, applying a combination of "divide and conquer" and "separation of concerns". The price that has to be paid, however, is extensive testing, frequent iterations in the design process, and the lack of guarantees for safety and performance properties.The second important factor in the creation of the priority program Kondiskwas the growing awareness of the need for a more comprehensive approach to hybrid systems both in the computer science and the control engineering communities, and the fact that important foundations had been laid in both camps -and sometimes across their borders as well. It was one of the key ideas in the call for proposals that the interaction of scientists from computer science and control engineering should be stimulated, and this resulted in several interdisciplinary projects. These projects not only led to interesting and novel results but generally created a deeper understanding of the complementary theories and issues on both sides. So...

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Section: Discrete Controllers For Hybrid Dynamic Systemsmentioning

confidence: 99%

Modelling, Analysis, and Design of Hybrid Systems

Engell¹,

Frehse²,

Schnieder³

2002

Lecture Notes in Control and Information Sciences

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“…Ç äåýôåñç åñãáóßá [80] äåß÷íåé åðßóçò ìå ìáèçìáôéêü ôñüðï üôé ôá ðåñéóóüôåñá ìïíôÝëá õâñéäéêþí óõóôÞìáôùí åßíáé éóïäýíáìá, üôáí ìïíôåëïðïéïýí õâñéäéêÜ óõóôÞìáôá ßäéáò ðïëõðëïêüôçôáò. [63,64], ôá ×ñïíéêÜ Ðñïãñáììáôéaeüìåíá Äßêôõá Petri (Programmable Timed Petri Nets) [119], ôá õøçëïý åðéðÝäïõ ÕâñéäéêÜ Äßêôõá Petri (High level Hybrid Petri Nets) [68,69], ôá ÕâñéäéêÜ Äßêôõá (Hybrid Nets) [39], ôá ÕâñéäéêÜ Äßêôõá Petri (Hybrid Petri Nets) [36,37,38], ôï ìïíôÝëï Äßêôõá Petri-Áëãåâñü-äéáöïñéêÝò åîéóþóåéò (Petri Nets-DAE) [31] • T åßíáé Ýíá ðåðåñáóìÝíï óýíïëï ìåôáâÜóåùí ãéá ôï ïðïßï éó÷ýåé |T | = m.…”

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confidence: 99%

Ανάλυση Ευστάθειας Υβριδικών Δυναμικών Συστημάτων

Δαβράζος¹

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An Environment for the Integrated Modelling of Systems with Complex Continuous and Discrete Dynamics

Remelhe

Engell

Otter³

et al.

Modelling, Analysis, and Design of Hybrid Systems

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Abstract. The modelling and simulation of sophisticated technical systems is a demanding task. On the one hand, the physical part consists of a large number of subsystems which exhibit predominantly continuous dynamics, sometimes with (infrequent) discontinuities. On the other hand, the distributed computerised control systems constitute complex discretetime and discrete-event systems that require completely different modelling and simulation methods. For an evaluation of the behaviour and the performance of the overall system, both types of models have to be combined and simulated efficiently. This contribution presents the requirements for a modelling environment for such systems and discusses an approach that consists of object-oriented modelling and efficient simulation of the physical part using the physical systems modelling language MODELICA, a software environment for the definition of discrete-event models using various formalisms, and the integration of both parts of the system via model translation. The coordination of both parts is performed by the MODELICA simulator. The modelling environment called DES/M (discrete-event systems for Modelica) supports the interoperation of different domain specific discrete-event formalisms. To illustrate the usage of the environment, a laboratory batch plant model is presented. A more elaborate example is described in another contribution in this volume (Mosterman et al., 2002).

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Model-based control synthesis of continuous-discrete systems

Cited by 4 publications

References 9 publications

Modelling, Analysis, and Design of Hybrid Systems

Modelling, Analysis, and Design of Hybrid Systems

Ανάλυση Ευστάθειας Υβριδικών Δυναμικών Συστημάτων

An Environment for the Integrated Modelling of Systems with Complex Continuous and Discrete Dynamics

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