Performance analysis and optimization of supervisory controllers

Generating the brain of complex manufacturing system

Component-wise Supervisory Controller Synthesis in a Client/Server Architecture

\u3cp\u3eThe manual design of monolithic controllers for flexible manufacturing systems is no longer feasible due to the sheer size of the problem. A well-known approach to tackle this scalability problem is to create a set of smaller controllers and orchestrate their interaction in an architecture. Another approach is to use synthesis techniques to generate a controller model from models of the uncontrolled system and the formalized requirements. In this paper we describe a pragmatic approach that combines the complementary advantages of these two approaches, where we decompose the design problem of the controller into a number of sub-controllers by introducing intermediate interfaces and use supervisory controller synthesis to synthesize the sub-controllers. We have evaluated this approach on an industrial case study, where we examined a large controller in a lithography machine. We found that the approach can successfully be used to generate a large portion of the needed sub-controllers.\u3c/p\u3

Partial-order reduction for performance analysis of max-plus timed systems

\u3cp\u3eThis paper presents a partial-order reduction method for performance analysis of max-plus timed systems. A max-plus timed system is a network of automata, where the timing behavior of deterministic system tasks (events in an automaton) is captured in (max, +) matrices. These tasks can be characterized in various formalisms like synchronous data flow, Petri nets, or real-time calculus. The timing behavior of the system is captured in a (max, +) state space, calculated from the composition of the automata. This state space may exhibit redundant interleaving with respect to performance aspects like throughput or latency. The goal of this work is to obtain a smaller state space to speed up performance analysis. To achieve this, we first formalize state-space equivalence with respect to throughput and latency analysis. Then, we present a way to compute a reduced composition directly from the specification. This yields a smaller equivalent state space. We perform the reduction on-the-fly, without first computing the full composition. Experiments show the effectiveness of the method on a set of realistic manufacturing system models.\u3c/p\u3

Exploring DSL evolutionary patterns in practice: a study of DSL evolution in a large-scale industrial DSL repository

\u3cp\u3eModel-driven engineering is used in the design of systems to (a.o.) enable analysis early in the design process. For instance, by using domain-specific languages, enabling engineers to model systems in terms of their domain, rather then encoding them into general purpose modeling languages. Domain-specific languages, like classical software, evolve over time. When domain languages evolve, they may trigger co-evolution of models, model-to-model transformations, editors (both graphical and textual), and other artifacts that depend on the domain-specific language. This co-evolution can be tedious and very costly. In literature, various approaches are proposed towards automated co-evolution. However, these approaches do not reach full automation. Several other studies have shown that there are theoretical limitations to the level of automation that can be achieved in certain scenarios. For several scenarios full automation can never be achieved. We wish to gain insight to which extent practically occurring scenarios can be automated. To gain this insight, in this paper, we investigate on a large-scale industrial repository, which (co-)evolutionary scenarios occur in practice, and compare them with the various scenarios and their theoretical automatability. We then assess whether practically occurring scenarios can be fully automated.\u3c/p\u3

Identifying bottlenecks in manufacturing systems using stochastic criticality analysis

\u3cp\u3eSystem design is a difficult process with many design-choices for which the impact may be difficult to foresee. Manufacturing system design is no exception to this. Increased use of flexible manufacturing systems which are able to perform different operations/use-cases further raises the design complexity. One important criterion to consider is the overall makespan and associated critical path for the different use-cases of the system. Stochastic critical path analysis plays a fundamental role in providing useful feedback for system designers to evaluate alternative specifications, which traditional fixed-time analysis cannot. In this paper, we extend our formal model-based framework, for the specification and design of manufacturing systems, with stochastic analysis abilities by associating a criticality index to each action performed by the system. This index can then be visualized and used within the framework such that a system designer can make better informed decisions. We propose a Monte-Carlo method as an estimation algorithm and we explicitly define and use confidence intervals to achieve an acceptable estimation error. We further demonstrate the use of the extended framework and stochastic analysis with an example manufacturing system.\u3c/p\u3

Compositional specification of functionality and timing of manufacturing systems

In this paper, a formal modeling approach is introduced for compositional specification of both functionality and timing of manufacturing systems. Functionality aspects can be considered orthogonally to the timing. The functional aspects are specified using two abstraction levels; high-level activities and lower level actions. Design of a functionally correct controller is possible by looking only at the activity level, abstracting from the different execution orders of actions. Furthermore, the specific timing of actions is not needed. As a result, controller design\u3cbr/\u3ecan be performed on a much smaller state space compared to an explicit model where timing and actions are present. The performance of the controller can be analyzed and optimized\u3cbr/\u3eby taking into account the timing characteristics. Since formal semantics are given in terms of a (max, +) state space, various existing performance analysis techniques can be used. We\u3cbr/\u3eillustrate the approach, including performance analysis, on an example manufacturing system

xCPS: a tool to explore cyber physical systems

Cyber-Physical Systems (CPS) play an important role in the modern high-tech industry. Designing such systems is an especially challenging task due to the multi-disciplinary nature of these systems, and the range of abstraction levels involved. To facilitate hands-on experience with such systems, we develop a cyber-physical platform that aids in both research and education on CPS. This paper describes this platform, which contains all typical CPS components. The platform is used in various research and education projects for bachelor, master, and PhD students. We discuss the platform and illustrate its use with a number of projects and the educational opportunities they provide