2,023 research outputs found
Model predictive control techniques for hybrid systems
This paper describes the main issues encountered when applying model predictive control to hybrid processes. Hybrid model predictive control (HMPC) is a research field non-fully developed with many open challenges. The paper describes some of the techniques proposed by the research community to overcome the main problems encountered. Issues related to the stability and the solution of the optimization problem are also discussed. The paper ends by describing the results of a benchmark exercise in which several HMPC schemes were applied to a solar air conditioning plant.Ministerio de Eduación y Ciencia DPI2007-66718-C04-01Ministerio de Eduación y Ciencia DPI2008-0581
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
Compositional nonblocking verificationusing generalised nonblocking abstractions
This paper proposes a method for compositional verification of the standard and generalized nonblocking properties of large discrete event systems. The method is efficient as it avoids the explicit construction of the complete state space by considering and simplifying individual subsystems before they are composed further. Simplification is done using a set of abstraction rules preserving generalized nonblocking equivalence, which are shown to be correct and computationally feasible. Experimental results demonstrate the suitability of the method to verify several large-scale discrete event systems models both for standard and generalized nonblocking
A Supervisory Control Algorithm Based on Property-Directed Reachability
We present an algorithm for synthesising a controller (supervisor) for a
discrete event system (DES) based on the property-directed reachability (PDR)
model checking algorithm. The discrete event systems framework is useful in
both software, automation and manufacturing, as problems from those domains can
be modelled as discrete supervisory control problems. As a formal framework,
DES is also similar to domains for which the field of formal methods for
computer science has developed techniques and tools. In this paper, we attempt
to marry the two by adapting PDR to the problem of controller synthesis. The
resulting algorithm takes as input a transition system with forbidden states
and uncontrollable transitions, and synthesises a safe and
minimally-restrictive controller, correct-by-design. We also present an
implementation along with experimental results, showing that the algorithm has
potential as a part of the solution to the greater effort of formal supervisory
controller synthesis and verification.Comment: 16 pages; presented at Haifa Verification Conference 2017, the final
publication is available at Springer via
https://doi.org/10.1007/978-3-319-70389-3_
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