A state-based framework for supervisory control synthesis and verification

Markovski, Jasen; Beek, D.A. van; Theunissen, R.J.M.; Jacobs, Karen; Rooda, J.E.

doi:10.1109/cdc.2010.5717095

Cited by 51 publications

(45 citation statements)

References 8 publications

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“…49.1 [12,9], which is a refinement and extension of the framework defined in [1]. Domain engineers define the desired overall system specification (Specification Controlled System in Fig.…”

Section: Model-based Systems Engineering Frameworkmentioning

confidence: 99%

“…The state labels are employed to keep track of the state of the plant, and can be referenced in the control requirements. We employ two types of state-based control requirements [9]: φ and e −→ =⇒ φ , for some some event e, and some Boolean formula φ over the state labels, using the logical operators ∧, ∨, ¬, and =⇒ . The first requirement type specifies an invariant φ that must hold for every state of the supervised system, whereas the second type specifies necessary conditions, given by φ , for enabling event e.…”

Section: Case Study: High-tech Printersmentioning

confidence: 99%

“…This enabled us to specify the complete set of coordination rules for the printing process. For a detailed discussion of this transformation, including a formal definition, proof of correctness, and details on the implementation, we refer the interested reader to [9]. As an illustration of the effectiveness of our method, a part of the case study modeled by 23 generalized control requirements, resulted in 500+ requirements in the original form.…”

Section: Research Contributionsmentioning

confidence: 99%

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Coordination Control of Complex Machines

Baeten

Beek

Markovski

et al. 2014

Coordination Control of Distributed Systems

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Control and coordination are important aspects of the development of complex machines due to an ever increasing demand for better functionality, quality, and performance. In WP6 of the C4C project we developed a synthesis-centric systems engineering framework suitable for supervisory coordination of complex systems. The framework was employed to synthesize and validate a supervisory coordinator for maintenance procedures for a prototype of a high-tech Océ printer, showing proof of concept and viability of the proposed framework. The supervisor eliminates undesired behavior that could occur as a result of undesired interaction of the distributed printer components. In this chapter, we discuss the model-based systems engineering framework that was employed for synthesis of the supervisor and we illustrate the modeling process. Background and MotivationIn the last few decades, control software development has taken a more central role due to the ever increasing complexity of the machines, demands for higher quality and performance, and improved safety and ease of use [5]. Traditionally, the control software requirements are formulated informally in some sort of specification documents by domain engineers, to be translated into control software by software engineers. This is a time-consuming and an error prone process, since control requirements are often ambiguous and change frequently, so the produced software needs to be validated against the machine. If validation fails, the code must be rewritten leading to a define-validate-redefine loop. This issue in control software design gave rise to supervisory control theory [11,2,3,6], where models of high-level supervisory controllers, referred to as supervisors, are synthesized automatically based upon a formal model of the uncontrolled system, known as plant, and a model of the control requirements. Supervisory controllers observe the discrete-event behavior of the system and make control decisions based on the observed information. The supervisory controller synthesis problem is to achieve the greatest possible allowed behavior, which is specified by the control requirements, based on a given observable behavior.By applying automated control software generation based upon formal behavioral models, we aim to:1. Shift the focus of software engineers from writing and debugging code to modeling the plant and the control requirements. 2. Increase the use of models. Software engineers need not think in terms of code, since it is generated automatically. Instead, they make the formal models in terms of behavior, thus improving their communication with the domain engineers and other involved parties. 3. Shorten the design loop. Adjustments in the control specifications result in model changes, followed by automated synthesis of control software, which is likely to be less time consuming than directly adapting control code. 4. Use the formal behavioral models for simulation. We can validate the supervisor before expensive prototypes are built increasing confidence ...

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“…49.1 [12,9], which is a refinement and extension of the framework defined in [1]. Domain engineers define the desired overall system specification (Specification Controlled System in Fig.…”

Section: Model-based Systems Engineering Frameworkmentioning

confidence: 99%

Section: Case Study: High-tech Printersmentioning

confidence: 99%

Section: Research Contributionsmentioning

confidence: 99%

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Coordination Control of Complex Machines

Baeten

Beek

Markovski

et al. 2014

Coordination Control of Distributed Systems

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“…To mitigate some of the above issues in the design and development of supervisory control software for high-tech complex machines, we propose to employ a synthesis-centric model-driven systems engineering framework developed in [12][13][14], depicted in Fig. 1.…”

Section: A Synthesis-centric Approachmentioning

confidence: 99%

The role of supervisory controller synthesis in automatic control software development

Baeten

Markovski

2015

Science of Computer Programming

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h i g h l i g h t s• We discuss the role of supervisor synthesis in automated software code generation.• The proposed approach is systematic and based on process theory.• We implemented a model-based systems and software engineering framework.• The framework has been applied to multiple industrial studies. a r t i c l e i n f o a b s t r a c t We give an overview of a model-driven systems engineering approach for high-tech systems that relies on supervisory controller synthesis. The proposed framework has a process-theoretic foundation and supports extensions with quantitative features. We briefly discuss several industrial case studies that highlight the advantages of the proposed approach.© 2013 Elsevier B.V. All rights reserved. Model-driven control software developmentEmbedding information and communication technology in consumer and industrial products was enabled by advances in software that carries most of these products' functionalities. The need for development techniques that can guarantee software quality is more than apparent. Conferences like Software Development Automation, Model-Driven Engineering Languages and Systems, or Applications of Concurrency in System Design, are some of the venues where this need has been recognized and studied by means of automated model-driven software development techniques. In this paper, we would like to point to one model-driven systems engineering approach, referred to as supervisory controller synthesis, which targets discrete-event control software for high-tech and complex systems. We find this approach to be relevant to the software development community and we hope that it might offer novel insights in development of quality control software, and bring the communities of software development, systems engineering, and formal methods closer together.

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“…In this way, the specification of the control logic is less vulnerable for changes in the physical system. An example of such work is the work on supervisory control synthesis by Rooda et al, e.g., in [83,100].…”

Section: Separating Design Rationale From Control Logicmentioning

confidence: 99%

Managing software complexity of adaptive systems

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A state-based framework for supervisory control synthesis and verification

Cited by 51 publications

References 8 publications

Coordination Control of Complex Machines

Coordination Control of Complex Machines

The role of supervisory controller synthesis in automatic control software development

Managing software complexity of adaptive systems

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