217 research outputs found
Approximately bisimilar symbolic models for nonlinear control systems
Control systems are usually modeled by differential equations describing how
physical phenomena can be influenced by certain control parameters or inputs.
Although these models are very powerful when dealing with physical phenomena,
they are less suitable to describe software and hardware interfacing the
physical world. For this reason there is a growing interest in describing
control systems through symbolic models that are abstract descriptions of the
continuous dynamics, where each "symbol" corresponds to an "aggregate" of
states in the continuous model. Since these symbolic models are of the same
nature of the models used in computer science to describe software and
hardware, they provide a unified language to study problems of control in which
software and hardware interact with the physical world. Furthermore the use of
symbolic models enables one to leverage techniques from supervisory control and
algorithms from game theory for controller synthesis purposes. In this paper we
show that every incrementally globally asymptotically stable nonlinear control
system is approximately equivalent (bisimilar) to a symbolic model. The
approximation error is a design parameter in the construction of the symbolic
model and can be rendered as small as desired. Furthermore if the state space
of the control system is bounded the obtained symbolic model is finite. For
digital control systems, and under the stronger assumption of incremental
input-to-state stability, symbolic models can be constructed through a suitable
quantization of the inputs.Comment: Corrected typo
Approximately bisimilar symbolic models for incrementally stable switched systems
Switched systems constitute an important modeling paradigm faithfully
describing many engineering systems in which software interacts with the
physical world. Despite considerable progress on stability and stabilization of
switched systems, the constant evolution of technology demands that we make
similar progress with respect to different, and perhaps more complex,
objectives. This paper describes one particular approach to address these
different objectives based on the construction of approximately equivalent
(bisimilar) symbolic models for switched systems. The main contribution of this
paper consists in showing that under standard assumptions ensuring incremental
stability of a switched system (i.e. existence of a common Lyapunov function,
or multiple Lyapunov functions with dwell time), it is possible to construct a
finite symbolic model that is approximately bisimilar to the original switched
system with a precision that can be chosen a priori. To support the
computational merits of the proposed approach, we use symbolic models to
synthesize controllers for two examples of switched systems, including the
boost DC-DC converter.Comment: 17 page
Towards Scalable Synthesis of Stochastic Control Systems
Formal control synthesis approaches over stochastic systems have received
significant attention in the past few years, in view of their ability to
provide provably correct controllers for complex logical specifications in an
automated fashion. Examples of complex specifications of interest include
properties expressed as formulae in linear temporal logic (LTL) or as automata
on infinite strings. A general methodology to synthesize controllers for such
properties resorts to symbolic abstractions of the given stochastic systems.
Symbolic models are discrete abstractions of the given concrete systems with
the property that a controller designed on the abstraction can be refined (or
implemented) into a controller on the original system. Although the recent
development of techniques for the construction of symbolic models has been
quite encouraging, the general goal of formal synthesis over stochastic control
systems is by no means solved. A fundamental issue with the existing techniques
is the known "curse of dimensionality," which is due to the need to discretize
state and input sets and that results in an exponential complexity over the
number of state and input variables in the concrete system. In this work we
propose a novel abstraction technique for incrementally stable stochastic
control systems, which does not require state-space discretization but only
input set discretization, and that can be potentially more efficient (and thus
scalable) than existing approaches. We elucidate the effectiveness of the
proposed approach by synthesizing a schedule for the coordination of two
traffic lights under some safety and fairness requirements for a road traffic
model. Further we argue that this 5-dimensional linear stochastic control
system cannot be studied with existing approaches based on state-space
discretization due to the very large number of generated discrete states.Comment: 22 pages, 3 figures. arXiv admin note: text overlap with
arXiv:1407.273
Synthesizing SystemC Code from Delay Hybrid CSP
Delay is omnipresent in modern control systems, which can prompt oscillations
and may cause deterioration of control performance, invalidate both stability
and safety properties. This implies that safety or stability certificates
obtained on idealized, delay-free models of systems prone to delayed coupling
may be erratic, and further the incorrectness of the executable code generated
from these models. However, automated methods for system verification and code
generation that ought to address models of system dynamics reflecting delays
have not been paid enough attention yet in the computer science community. In
our previous work, on one hand, we investigated the verification of delay
dynamical and hybrid systems; on the other hand, we also addressed how to
synthesize SystemC code from a verified hybrid system modelled by Hybrid CSP
(HCSP) without delay. In this paper, we give a first attempt to synthesize
SystemC code from a verified delay hybrid system modelled by Delay HCSP
(dHCSP), which is an extension of HCSP by replacing ordinary differential
equations (ODEs) with delay differential equations (DDEs). We implement a tool
to support the automatic translation from dHCSP to SystemC
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