5,516 research outputs found
Supervisory Control of Fuzzy Discrete Event Systems
In order to cope with situations in which a plant's dynamics are not
precisely known, we consider the problem of supervisory control for a class of
discrete event systems modelled by fuzzy automata. The behavior of such
discrete event systems is described by fuzzy languages; the supervisors are
event feedback and can disable only controllable events with any degree. The
concept of discrete event system controllability is thus extended by
incorporating fuzziness. In this new sense, we present a necessary and
sufficient condition for a fuzzy language to be controllable. We also study the
supremal controllable fuzzy sublanguage and the infimal controllable fuzzy
superlanguage when a given pre-specified desired fuzzy language is
uncontrollable. Our framework generalizes that of Ramadge-Wonham and reduces to
Ramadge-Wonham framework when membership grades in all fuzzy languages must be
either 0 or 1. The theoretical development is accompanied by illustrative
numerical examples.Comment: 12 pages, 2 figure
Similarity-Based Supervisory Control of Discrete Event Systems
Due to the appearance of uncontrollable events in discrete event systems, one
may wish to replace the behavior leading to the uncontrollability of
pre-specified language by some quite similar one. To capture this similarity,
we introduce metric to traditional supervisory control theory and generalize
the concept of original controllability to \ld-controllability, where \ld
indicates the similarity degree of two languages. A necessary and sufficient
condition for a language to be \ld-controllable is provided. We then examine
some properties of \ld-controllable languages and present an approach to
optimizing a realization.Comment: 22 pages, 5 figure
State-Based Control of Fuzzy Discrete Event Systems
To effectively represent possibility arising from states and dynamics of a
system, fuzzy discrete event systems as a generalization of conventional
discrete event systems have been introduced recently. Supervisory control
theory based on event feedback has been well established for such systems.
Noting that the system state description, from the viewpoint of specification,
seems more convenient, we investigate the state-based control of fuzzy discrete
event systems in this paper. We first present an approach to finding all fuzzy
states that are reachable by controlling the system. After introducing the
notion of controllability for fuzzy states, we then provide a necessary and
sufficient condition for a set of fuzzy states to be controllable. We also find
that event-based control and state-based control are not equivalent and further
discuss the relationship between them. Finally, we examine the possibility of
driving a fuzzy discrete event system under control from a given initial state
to a prescribed set of fuzzy states and then keeping it there indefinitely.Comment: 14 double column pages; 4 figures; to be published in the IEEE
Transactions on Systems, Man, and Cybernetics--Part B: Cybernetic
Supervisory Control of Fuzzy Discrete Event Systems: A Formal Approach
Fuzzy {\it discrete event systems} (DESs) were proposed recently by Lin and
Ying [19], which may better cope with the real-world problems with fuzziness,
impreciseness, and subjectivity such as those in biomedicine. As a continuation
of [19], in this paper we further develop fuzzy DESs by dealing with
supervisory control of fuzzy DESs. More specifically, (i) we reformulate the
parallel composition of crisp DESs, and then define the parallel composition of
fuzzy DESs that is equivalent to that in [19]; {\it max-product} and {\it
max-min} automata for modeling fuzzy DESs are considered; (ii) we deal with a
number of fundamental problems regarding supervisory control of fuzzy DESs,
particularly demonstrate controllability theorem and nonblocking
controllability theorem of fuzzy DESs, and thus present the conditions for the
existence of supervisors in fuzzy DESs; (iii) we analyze the complexity for
presenting a uniform criterion to test the fuzzy controllability condition of
fuzzy DESs modeled by max-product automata; in particular, we present in detail
a general computing method for checking whether or not the fuzzy
controllability condition holds, if max-min automata are used to model fuzzy
DESs, and by means of this method we can search for all possible fuzzy states
reachable from initial fuzzy state in max-min automata; also, we introduce the
fuzzy -controllability condition for some practical problems; (iv) a number
of examples serving to illustrate the applications of the derived results and
methods are described; some basic properties related to supervisory control of
fuzzy DESs are investigated. To conclude, some related issues are raised for
further consideration
DESIGN OF OPTIMAL PROCEDURAL CONTROLLERS FOR CHEMICAL PROCESSES MODELLED AS STOCHASTIC DISCRETE EVENT SYSTEMS
This thesis presents a formal method for the the design of optimal and provably correct
procedural controllers for chemical processes modelled as Stochastic Discrete Event Systems
(SDESs). The thesis extends previous work on Procedural Control Theory (PCT) [1],
which used formal techniques for the design of automation Discrete Event Systems (DESs).
Many dynamic processes for example, batch operations and the start-up and shut down of
continuous plants, can be modelled as DESs. Controllers for these systems are typically
of the sequential type.
Most prior work on characterizing the behaviour of DESs has been restricted to deterministic
systems. However, DESs consisting of concurrent interacting processes present
a broad spectrum of uncertainty such as uncertainty in the occurrence of events. The
formalism of weighted probabilistic Finite State Machine (wp-FSM) is introduced for
modelling SDESs and pre-de ned failure models are embedded in wp-FSM to describe
and control the abnormal behaviour of systems. The thesis presents e cient algorithms
and procedures for synthesising optimal procedural controllers for such SDESs.
The synthesised optimal controllers for such stochastic systems will take into consideration
probabilities of events occurrence, operation costs and failure costs of events in
making optimal choices in the design of control sequences. The controllers will force the
system from an initial state to one or more goal states with an optimal expected cost and
when feasible drive the system from any state reached after a failure to goal states.
On the practical side, recognising the importance of the needs of the target end
user, the design of a suitable software implementation is completed. The potential of both
the approach and the supporting software are demonstrated by two industry case studies.
Furthermore, the simulation environment gPROMS was used to test whether the operating
speci cations thus designed were met in a combined discrete/continuous environment
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