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Modular supervisory controller for complex systems
Automation for the oil and gas industry is driven by the need to improve efficiency, productivity, consistency, and personnel safety, while reducing cost. Fully automated systems alleviate the physical toll on human operators and allow them to focus on monitoring unsafe well events and machinery maintenance. Complex systems like drilling rigs and snubbing units require supervisory controllers that can safely coordinate equipment and processes, overcome interoperability challenges and allow for functional scalability without sacrificing safety, security, and consistency of operations. The primary objective of this report is to explore the feasibility of developing a modular supervisory controller architecture which addresses these concerns by modifying and extending existing architectures. Such modifications include the use of non-homogeneous models in sub-system modules, including discrete event models for control and physics-based models for collision avoidance, addition of a system compilation module (Meta Module) to identify simple design errors, and implementation of an algorithm for synthesis of modules and filters to replace missing sub-systems. This report discusses the implementation results of the modular supervisory control architecture (modMFSM) on a simplified two-machine drilling system for assessment of design practices. Simulations for three test cases were executed to assess the ability of the controller to correctly perform error-free operations, detect and react to possible collisions, and adapt to missing equipment. The report then discusses the possibilities of extending the modMFSM architecture to control large complex systems such as drilling rigs, using snubbing operations as an example.Mechanical Engineerin
A formally verified compiler back-end
This article describes the development and formal verification (proof of
semantic preservation) of a compiler back-end from Cminor (a simple imperative
intermediate language) to PowerPC assembly code, using the Coq proof assistant
both for programming the compiler and for proving its correctness. Such a
verified compiler is useful in the context of formal methods applied to the
certification of critical software: the verification of the compiler guarantees
that the safety properties proved on the source code hold for the executable
compiled code as well
Clafer: Lightweight Modeling of Structure, Behaviour, and Variability
Embedded software is growing fast in size and complexity, leading to intimate
mixture of complex architectures and complex control. Consequently, software
specification requires modeling both structures and behaviour of systems.
Unfortunately, existing languages do not integrate these aspects well, usually
prioritizing one of them. It is common to develop a separate language for each
of these facets. In this paper, we contribute Clafer: a small language that
attempts to tackle this challenge. It combines rich structural modeling with
state of the art behavioural formalisms. We are not aware of any other modeling
language that seamlessly combines these facets common to system and software
modeling. We show how Clafer, in a single unified syntax and semantics, allows
capturing feature models (variability), component models, discrete control
models (automata) and variability encompassing all these aspects. The language
is built on top of first order logic with quantifiers over basic entities (for
modeling structures) combined with linear temporal logic (for modeling
behaviour). On top of this semantic foundation we build a simple but expressive
syntax, enriched with carefully selected syntactic expansions that cover
hierarchical modeling, associations, automata, scenarios, and Dwyer's property
patterns. We evaluate Clafer using a power window case study, and comparing it
against other notations that substantially overlap with its scope (SysML, AADL,
Temporal OCL and Live Sequence Charts), discussing benefits and perils of using
a single notation for the purpose
Verification of logical consistency in robotic reasoning
Most autonomous robotic agents use logic inference to keep themselves to safe and permitted behaviour. Given a set of rules, it is important that the robot is able to establish the consistency between its rules, its perception-based beliefs, its planned actions and their consequences. This paper investigates how a robotic agent can use model checking to examine the consistency of its rules, beliefs and actions. A rule set is modelled by a Boolean evolution system with synchronous semantics, which can be translated into a labelled transition system (LTS). It is proven that stability and consistency can be formulated as computation tree logic (CTL) and linear temporal logic (LTL) properties. Two new algorithms are presented to perform realtime consistency and stability checks respectively. Their implementation provides us a computational tool, which can form the basis of efficient consistency checks on-board robots
Formal Specification and Verification for Automated Production Systems
Complex industrial control software often drives safety- and mission-critical
systems, like automated production plants or control units embedded into devices in automotive systems. Such controllers have in common that they are reactive systems, i.e., that they periodically read sensor stimuli and cyclically execute the same program to produce actuator signals.
The correctness of software for automated production is rarely verified using
formal techniques. Although, due to the Industrial Revolution 4.0 (IR4.0), the
impact and importance of software have become an important role in industrial automation.
What is used instead in industrial practice today is testing and simulation,
where individual test cases are used to validate an automated production system.
Three reasons why formal methods are not popular are: (a) It is difficult to
adequately formulate the desired temporal properties. (b) There is a lack of
specification languages for reactive systems that are both sufficiently
expressive and comprehensible for practitioners. (c) Due to the lack of an
environment model the obtained results are imprecise. Nonetheless, formal
methods for automated production systems are well studied academically---mainly on the verification of safety properties via model checking.
In this doctoral thesis we present the concept of (1) generalized test tables
(GTTs), a new specification language for functional properties, and their
extension (2) relational test tables (RTTs) for relational properties. The
concept includes the syntactical notion, designed for the intuition of
engineers, and the semantics, which are based on game theory. We use RTTs for a novel confidential property on reactive systems, the provably forgetting of information. Moreover, for regression verification, an important relational
property, we are able to achieve performance improvements by (3) creating
a decomposing rule which splits large proofs into small sub-task. We implemented the verification procedures and evaluated them against realistic case studies, e.g., the Pick-and-Place-Unit from the Technical University of Munich.
The presented contribution follows the idea of lowering the obstacle of
verifying the dependability of reactive systems in general, and automated
production systems in particular for the engineer either by introducing a new
specification language (GTTs), by exploiting existing programs for the
specification (RTTs, regression verification), or by improving the verification
performance
Tools and Algorithms for the Construction and Analysis of Systems
This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems
Simulation and statistical model-checking of logic-based multi-agent system models
This thesis presents SALMA (Simulation and Analysis of Logic-Based Multi-
Agent Models), a new approach for simulation and statistical model checking
of multi-agent system models.
Statistical model checking is a relatively new branch of model-based approximative
verification methods that help to overcome the well-known scalability
problems of exact model checking. In contrast to existing solutions,
SALMA specifies the mechanisms of the simulated system by means of logical
axioms based upon the well-established situation calculus. Leveraging
the resulting first-order logic structure of the system model, the simulation
is coupled with a statistical model-checker that uses a first-order variant of
time-bounded linear temporal logic (LTL) for describing properties. This is
combined with a procedural and process-based language for describing agent
behavior. Together, these parts create a very expressive framework for modeling
and verification that allows direct fine-grained reasoning about the agents’
interaction with each other and with their (physical) environment.
SALMA extends the classical situation calculus and linear temporal logic
(LTL) with means to address the specific requirements of multi-agent simulation
models. In particular, cyber-physical domains are considered where
the agents interact with their physical environment. Among other things,
the thesis describes a generic situation calculus axiomatization that encompasses
sensing and information transfer in multi agent systems, for instance
sensor measurements or inter-agent messages. The proposed model explicitly
accounts for real-time constraints and stochastic effects that are inevitable in
cyber-physical systems.
In order to make SALMA’s statistical model checking facilities usable also
for more complex problems, a mechanism for the efficient on-the-fly evaluation
of first-order LTL properties was developed. In particular, the presented algorithm
uses an interval-based representation of the formula evaluation state
together with several other optimization techniques to avoid unnecessary computation.
Altogether, the goal of this thesis was to create an approach for simulation
and statistical model checking of multi-agent systems that builds upon
well-proven logical and statistical foundations, but at the same time takes a
pragmatic software engineering perspective that considers factors like usability,
scalability, and extensibility. In fact, experience gained during several small
to mid-sized experiments that are presented in this thesis suggest that the
SALMA approach seems to be able to live up to these expectations.In dieser Dissertation wird SALMA (Simulation and Analysis of Logic-Based
Multi-Agent Models) vorgestellt, ein im Rahmen dieser Arbeit entwickelter
Ansatz für die Simulation und die statistische Modellprüfung (Model Checking)
von Multiagentensystemen.
Der Begriff „Statistisches Model Checking” beschreibt modellbasierte approximative
Verifikationsmethoden, die insbesondere dazu eingesetzt werden
können, um den unvermeidlichen Skalierbarkeitsproblemen von exakten Methoden
zu entgehen. Im Gegensatz zu bisherigen Ansätzen werden in SALMA die
Mechanismen des simulierten Systems mithilfe logischer Axiome beschrieben,
die auf dem etablierten Situationskalkül aufbauen. Die dadurch entstehende
prädikatenlogische Struktur des Systemmodells wird ausgenutzt um ein Model
Checking Modul zu integrieren, das seinerseits eine prädikatenlogische Variante
der linearen temporalen Logik (LTL) verwendet. In Kombination mit
einer prozeduralen und prozessorientierten Sprache für die Beschreibung von
Agentenverhalten entsteht eine ausdrucksstarke und flexible Plattform für die
Modellierung und Verifikation von Multiagentensystemen. Sie ermöglicht eine
direkte und feingranulare Beschreibung der Interaktionen sowohl zwischen
Agenten als auch von Agenten mit ihrer (physischen) Umgebung.
SALMA erweitert den klassischen Situationskalkül und die lineare temporale
Logik (LTL) um Elemente und Konzepte, die auf die spezifischen Anforderungen
bei der Simulation und Modellierung von Multiagentensystemen
ausgelegt sind. Insbesondere werden cyber-physische Systeme (CPS) unterstützt,
in denen Agenten mit ihrer physischen Umgebung interagieren. Unter
anderem wird eine generische, auf dem Situationskalkül basierende, Axiomatisierung
von Prozessen beschrieben, in denen Informationen innerhalb von
Multiagentensystemen transferiert werden – beispielsweise in Form von Sensor-
Messwerten oder Netzwerkpaketen. Dabei werden ausdrücklich die unvermeidbaren
stochastischen Effekte und Echtzeitanforderungen in cyber-physischen
Systemen berücksichtigt.
Um statistisches Model Checking mit SALMA auch für komplexere Problemstellungen
zu ermöglichen, wurde ein Mechanismus für die effiziente Auswertung
von prädikatenlogischen LTL-Formeln entwickelt. Insbesondere beinhaltet
der vorgestellte Algorithmus eine Intervall-basierte Repräsentation des
Auswertungszustands, sowie einige andere Optimierungsansätze zur Vermeidung
von unnötigen Berechnungsschritten.
Insgesamt war es das Ziel dieser Dissertation, eine Lösung für Simulation
und statistisches Model Checking zu schaffen, die einerseits auf fundierten
logischen und statistischen Grundlagen aufbaut, auf der anderen Seite jedoch
auch pragmatischen Gesichtspunkten wie Benutzbarkeit oder Erweiterbarkeit
genügt. Tatsächlich legen erste Ergebnisse und Erfahrungen aus
mehreren kleinen bis mittelgroßen Experimenten nahe, dass SALMA diesen
Zielen gerecht wird
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