Supervision equivalence

This paper presents a general framework for modular synthesis of supervisors for discrete event systems. The approach is based on compositional minimisation, using concepts of process equivalence. Its result is a compact representation of a least restrictive supervisor that ensures controllability and nonblocking. The method is demonstrated to reduce the number of states to be constructed for a simple manufacturing example, and the framework is proven to be sound

Modular nonblocking verification using conflict equivalence

This paper proposes a modular approach to verifying whether a large discrete event system is nonconflicting. The new approach avoids computing the synchronous product of a large set of finite-state machines. Instead, the synchronous product is computed gradually, and intermediate results are simplified using conflict-preserving abstractions based on process-algebraic results about fair testing. Heuristics are used to choose between different possible abstractions. Experimental results show that the method is applicable to finite-state machine models of industrial scale and brings considerable improvements in performance over other methods

Compositional synthesis of discrete event systems via synthesis equivalence

A two-pass algorithm for compositional synthesis of modular supervisors for largescale systems of composed finite-state automata is proposed. The first pass provides an efficient method to determine whether a supervisory control problem has a solution, without explicitly constructing the synchronous composition of all components. If a solution exists, the second pass yields an over-approximation of the least restrictive solution which, if nonblocking, is a modular representation of the least restrictive supervisor. Using a new type of equivalence of nondeterministic processes, called synthesis equivalence, a wide range of abstractions can be employed to mitigate state-space explosion throughout the algorithm

Conflicts and projections

This paper studies abstraction methods suitable to verify very large models of discrete-event systems to be nonconflicting. It compares the observer property to methods known from process algebra, namely to conflict equivalence and observation equivalence. The observer property is shown to be the property that corresponds to conflict equivalence in the case where natural projection is used for abstraction. In this case, the observer property turns out to be the least restrictive condition that can be imposed on natural projection to enable compositional reasoning about conflicts. The observer property is also shown to be closely related to observation equivalence. Several examples and propositions are presented to relate different aspects of these methods of abstraction

Compositional synthesis of maximally permissive supervisors using supervision equivalence

This paper presents a general framework for efficient synthesis of supervisors for discrete event systems. The approach is based on compositional minimisation, using concepts of process equivalence. In this context, a large number of ways are suggested how a finite-state automaton can be simplified such that the results of supervisor synthesis are preserved. The proposed approach yields a compact representation of a least restrictive supervisor that ensures controllability and nonblocking. The method is demonstrated on a simple manufacturing example to significantly reduce the number of states constructed for supervisor synthesis

Supremica – An integrated environment for verification, synthesis and simulation of discrete event systems

An integrated environment, Supremica, for verification, synthesis and simulation of discrete event systems is presented. The basic model in Supremica is finite automata where the transitions have an associated event together with a guard condition and an action function that updates automata variables. Supremica uses two main approaches to handle large state-spaces. The first approach exploits modularity in order to divide the original problem into many smaller problems that together solve the original problem. The second approach uses an efficient data structure, a binary decision diagram, to symbolically represent the reachable states. Models in Supremica may be simulated in the environment. It is also possible to generate code that implements the behavior of the model using both the IEC 61131 and the IEC 61499 standard

Supremica-An Efficient Tool for Large-Scale Discrete Event Systems

Supremica is a tool for the modelling and analysis of discrete-event control functions based on state machine models of the uncontrolled plant and specification of the desired closed-loop behaviour. The modelling framework in Supremica is based on finite-state machines extended with variables, guard conditions, and action functions. In order to handle large-scale problems of industrially interesting size, Supremica uses advanced model checking techniques such as symbolic representations and compositional abstraction. Supremica has been used in several industrial research projects to verify and synthesise control functions for embedded controllers, industrial robots, and flexible manufacturing systems, and to verify program code for autonomous vehicles. This paper gives an overview of the modelling features of Supremica, shows the verification and synthesis facilities and their performance for large problems, and presents some of the industrial applications where Supremica has been used

Compositional Approaches in Supervisory Control with Application to Automatic Generation of Robot Interlocking Policies

The work presented in this thesis concerns verification and synthesis in the Ramadge and Wonham supervisory control framework. Supervisory control constitutes a formal framework for the design of supervisors for discrete event systems. These systems usually model high level descriptions of logical behaviours in applications such as flexible manufacturing processes, chemical batch processing systems and communication systems. The supervisory control framework has the potential to solve many safety and flexibility issues in such systems. Unfortunately, the analysis of discrete event systems involves an intrinsic difficulty known as the state-space explosion problem---a combinatorial explosion that soon occurs when problems of real-world complexity are analysed. The state-space explosion problem has given rise to much research and in the last decades many ingenious approaches to solving the problem have been presented. However, most of these approaches have in common that they can only be applied to special classes of supervisory control problems or that they only give partial solutions.Therefore, in a new attempt to overcome the state-space explosion problem for general supervisory control problems, this thesis develops compositional methods for verification and synthesis in the supervisory control framework. Compositional methods exploit the inherent modularity of discrete event models by using abstractions to incrementally hide already analysed behaviour of the system. A major part of the thesis concerns developing a methodology for calculating these abstractions and for applying the compositional approach to complex problems. Furthermore, a very important part of this work is the implementation of the compositional methods in a software tool for supervisory control. Experimental results from this implementation are also presented in the thesis.As a matter of fact, earlier work on computational complexity have shown that it is impossible to solve the state-space explosion problem efficiently for general problems. Even so, the results presented in this thesis show that ``large\u27\u27 supervisory control problems found in the litterature typically have enough structure in them to be solved efficiently by compositional methods.Another contribution of this thesis is the development of a method to automatically generate models of the necessary interlocking requirements with respect to robot collisions in industrial robot cells. The generated models are suitable for supervisor synthesis in the supervisory control framework as well as for work-cycle optimisation. Automatic model generation and synthesis are important factors for shortening the development time and improving the flexibility for industrial robot cells