Limited Lookahead Policies for Robust Supervisory Control of Discrete Event Systems

In this thesis, Limited Lookahead Policies (LLP) have been developed for Robust Nonblocking Supervisory Control Problem (RNSCP) of discrete event systems. In the robust control problem considered here, the plant model is assumed to belong to a given finite set of DES models. The introduced supervisor computes the control action in online fashion and it is named Robust Limited Lookahead (RLL) supervisor. In comparison with offline supervisory control, RLL supervisor can reduce the complexity associated with the computation of control law as it looks at the behavior of system at the current state and of a limited depth in future. Since a conservative policy is adopted here, the behavior of the system under supervision of the RLL supervisor is generally more restrictive than the optimal offline supervisor. A sufficient condition is presented under which a limited lookahead window can guarantee the optimality (maximal permissiveness) of the RLL supervisor. In some problems, the required window length for maximally permissive RLL supervisor may become unbounded. To overcome this limitation RNSCP with State information (RNSCP-S) is studied and solved resulting in a state-based RLL (RLL-S) supervisor. The results of this thesis can be regarded as an extension of previous work in the literature on limited lookahead policies for (non-robust) supervisory control to the case of nonblocking robust supervisory control. The robust limited lookahead design procedures are implemented in MATLAB environment and applied to two examples involving spacecraft propulsion systems

Fault recovery in discrete-event systems with intermittent and permanent failures

As systems grow more complex to cater to demanding operational requirements, they tend to suffer from increasing component failures. It is important to minimize the effect of these failures on the overall performance of these systems. In this thesis, fault recovery using discrete event systems theory is studied. It is assumed that the plant can be modeled as a finite state automaton, and that is prone to failures. For this study all events are assumed observable and the extension to the case of partial observation is left for future research. The problem of the synthesis of fault recovery procedures is studied. In particular, the cases are studied in which the plant may return to normal operation. This could be either because the failures are intermittent or because the plant has the capacity to repair or reset. Both of the above cases are studied in this thesis. It turns out that the problem is an instance of the problem of robust nonblocking supervisory control for countably infinite number of plants. The objective of the thesis is to obtain maximally permissive solution for the above problem. It is shown that the desired supervisor can be obtained as the maximally permissive solution of a robust control problem involving a bounded number of plants. Furthermore, an iterative procedure is provided to solve the original problem involving an infinite number of plants. The procedure is guaranteed to converge in a bounded number of steps. Several examples are provided to illustrate the proposed procedure

Robust State-Based Supervisory Control of Hierarchical Discrete-Event Systems

Model uncertainty due to unknown dynamics or changes (such as faults) must be addressed in supervisory control design. Robust supervisory control, one of the approaches to handle model uncertainty, provides a solution (i.e., supervisor) that simultaneously satisfies the design objectives of all possible known plant models. Complexity has always been a challenging issue in the supervisory control of discrete-event systems, and different methods have been proposed to mitigate it. The proposed methods aim to handle complexity either through a structured solution (e.g. decentralized supervision) or by taking advantage of computationally efficient structured models for plants (e.g., hierarchical models). One of the proposed hierarchical plant model formalisms is State-Tree-Structure (STS), which has been successfully used in supervisor design for systems containing up to 10^20 states. In this thesis, a robust supervisory control framework is developed for systems modeled by STS. First, a robust nonblocking supervisory control problem is formulated in which the plant model belongs to a finite set of automata models and design specifications are expressed in terms of state sets. A state-based approach to supervisor design is more convenient for implementation using symbolic calculation tools such as Binary Decision Diagrams (BDDs). In order to ensure that the set of solutions for robust control problem can be obtained from State Feedback Control (SFBC) laws and hence suitable for symbolic calculations, it is assumed, without loss of generality, that the plant models satisfy a mutual refinement assumption. In this thesis, a set of necessary and sufficient conditions is derived for the solvability of the robust control problem, and a procedure for finding the maximally permissive solution is obtained. Next, the robust state-based supervisory framework is extended to systems modeled by STS. A sufficient condition is provided under which the mutual refinement property can be verified without converting the hierarchical model of STS to a flat automaton model. As an illustrative example, the developed approach was successfully used to design a robust supervisor for a Flexible Manufacturing System (FMS) with a state set of order 10^8

Distributed Nonblocking Supervisory Control of Timed Discrete-Event Systems with Communication Delays and Losses

This paper investigates the problem of distributed nonblocking supervisory control for timed discrete-event systems (DESs). The distributed supervisors communicate with each other over networks subject to nondeterministic communication delays and losses. Given that the delays are counted by time, techniques have been developed to model the dynamics of the communication channels. By incorporating the dynamics of the communication channels into the system model, we construct a communication automaton to model the interaction process between the supervisors. Based on the communication automaton, we define the observation mappings for the supervisors, which consider delays and losses occurring in the communication channels. Then, we derive the necessary and sufficient conditions for the existence of a set of supervisors for distributed nonblocking supervisory control. These conditions are expressed as network controllability, network joint observability, and system language closure. Finally, an example of intelligent manufacturing is provided to show the application of the proposed framework

INCREMENTAL FAULT DIAGNOSABILITY AND SECURITY/PRIVACY VERIFICATION

Dynamical systems can be classified into two groups. One group is continuoustime systems that describe the physical system behavior, and therefore are typically modeled by differential equations. The other group is discrete event systems (DES)s that represent the sequential and logical behavior of a system. DESs are therefore modeled by discrete state/event models.DESs are widely used for formal verification and enforcement of desired behaviors in embedded systems. Such systems are naturally prone to faults, and the knowledge about each single fault is crucial from safety and economical point of view. Fault diagnosability verification, which is the ability to deduce about the occurrence of all failures, is one of the problems that is investigated in this thesis. Another verification problem that is addressed in this thesis is security/privacy. The two notions currentstate opacity and current-state anonymity that lie within this category, have attracted great attention in recent years, due to the progress of communication networks and mobile devices.Usually, DESs are modular and consist of interacting subsystems. The interaction is achieved by means of synchronous composition of these components. This synchronization results in large monolithic models of the total DES. Also, the complex computations, related to each specific verification problem, add even more computational complexity, resulting in the well-known state-space explosion problem.To circumvent the state-space explosion problem, one efficient approach is to exploit the modular structure of systems and apply incremental abstraction. In this thesis, a unified abstraction method that preserves temporal logic properties and possible silent loops is presented. The abstraction method is incrementally applied on the local subsystems, and it is proved that this abstraction preserves the main characteristics of the system that needs to be verified.The existence of shared unobservable events means that ordinary incremental abstraction does not work for security/privacy verification of modular DESs. To solve this problem, a combined incremental abstraction and observer generation is proposed and analyzed. Evaluations show the great impact of the proposed incremental abstraction on diagnosability and security/privacy verification, as well as verification of generic safety and liveness properties. Thus, this incremental strategy makes formal verification of large complex systems feasible

Formal techniques for the procedural control of industrial processes

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Robust decentralized supervisory control of discrete-event systems

In this thesis we study robust supervisory control of discrete event systems in two different settings. First, we consider the problem of synthesizing a set of decentralized supervisors when the precise model of the plant is not known, but it is known that it is among a finite set of plant models. To tackle this problem, we form the union of all possible behaviors and construct an appropriate specification, from the given set of specifications, and solve the conventional decentralized supervisory control associated with it. We also prove that the given robust problem has a solution if and only if this conventional decentralized supervisory control problem has a solution. In another setting, we investigate the problem of synthesizing a set of communicating supervisors in the presence of delay in communication channels, and call it Unbounded Communication Delay Robust Supervisory Control problem (UCDR-SC problem). In this problem, We assume that delay is unbounded but it is finite, meaning that any message sent from a local supervisor will be received by any other local supervisors after a finite but unknown delay. To solve this problem, we redefine the supervisory decision making rules, introduce a new language property called unbounded-communication-delay-robust (UCDR), and present a set of conditions on the specification of the problem. We also show that the new class of languages that is the solution to this problem has some interesting relations with other observational languages