2,921 research outputs found
On Model Based Synthesis of Embedded Control Software
Many Embedded Systems are indeed Software Based Control Systems (SBCSs), that
is control systems whose controller consists of control software running on a
microcontroller device. This motivates investigation on Formal Model Based
Design approaches for control software. Given the formal model of a plant as a
Discrete Time Linear Hybrid System and the implementation specifications (that
is, number of bits in the Analog-to-Digital (AD) conversion)
correct-by-construction control software can be automatically generated from
System Level Formal Specifications of the closed loop system (that is, safety
and liveness requirements), by computing a suitable finite abstraction of the
plant.
With respect to given implementation specifications, the automatically
generated code implements a time optimal control strategy (in terms of set-up
time), has a Worst Case Execution Time linear in the number of AD bits , but
unfortunately, its size grows exponentially with respect to . In many
embedded systems, there are severe restrictions on the computational resources
(such as memory or computational power) available to microcontroller devices.
This paper addresses model based synthesis of control software by trading
system level non-functional requirements (such us optimal set-up time, ripple)
with software non-functional requirements (its footprint). Our experimental
results show the effectiveness of our approach: for the inverted pendulum
benchmark, by using a quantization schema with 12 bits, the size of the small
controller is less than 6% of the size of the time optimal one.Comment: Accepted for publication by EMSOFT 2012. arXiv admin note:
substantial text overlap with arXiv:1107.5638,arXiv:1207.409
A Map-Reduce Parallel Approach to Automatic Synthesis of Control Software
Many Control Systems are indeed Software Based Control Systems, i.e. control
systems whose controller consists of control software running on a
microcontroller device. This motivates investigation on Formal Model Based
Design approaches for automatic synthesis of control software.
Available algorithms and tools (e.g., QKS) may require weeks or even months
of computation to synthesize control software for large-size systems. This
motivates search for parallel algorithms for control software synthesis.
In this paper, we present a Map-Reduce style parallel algorithm for control
software synthesis when the controlled system (plant) is modeled as discrete
time linear hybrid system. Furthermore we present an MPI-based implementation
PQKS of our algorithm. To the best of our knowledge, this is the first parallel
approach for control software synthesis.
We experimentally show effectiveness of PQKS on two classical control
synthesis problems: the inverted pendulum and the multi-input buck DC/DC
converter. Experiments show that PQKS efficiency is above 65%. As an example,
PQKS requires about 16 hours to complete the synthesis of control software for
the pendulum on a cluster with 60 processors, instead of the 25 days needed by
the sequential algorithm in QKS.Comment: To be submitted to TACAS 2013. arXiv admin note: substantial text
overlap with arXiv:1207.4474, arXiv:1207.409
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
Model Based Synthesis of Control Software from System Level Formal Specifications
Many Embedded Systems are indeed Software Based Control Systems, that is
control systems whose controller consists of control software running on a
microcontroller device. This motivates investigation on Formal Model Based
Design approaches for automatic synthesis of embedded systems control software.
We present an algorithm, along with a tool QKS implementing it, that from a
formal model (as a Discrete Time Linear Hybrid System) of the controlled system
(plant), implementation specifications (that is, number of bits in the
Analog-to-Digital, AD, conversion) and System Level Formal Specifications (that
is, safety and liveness requirements for the closed loop system) returns
correct-by-construction control software that has a Worst Case Execution Time
(WCET) linear in the number of AD bits and meets the given specifications.
We show feasibility of our approach by presenting experimental results on
using it to synthesize control software for a buck DC-DC converter, a widely
used mixed-mode analog circuit, and for the inverted pendulum.Comment: Accepted for publication by ACM Transactions on Software Engineering
and Methodology (TOSEM
On minimising the maximum expected verification time
Cyber Physical Systems (CPSs) consist of hardware and software components. To verify that the whole (i.e., software + hardware) system meets the given specifications, exhaustive simulation-based approaches (Hardware In the Loop Simulation, HILS) can be effectively used by first generating all relevant simulation scenarios (i.e., sequences of disturbances) and then actually simulating all of them (verification phase). When considering the whole verification activity, we see that the above mentioned verification phase is repeated until no error is found. Accordingly, in order to minimise the time taken by the whole verification activity, in each verification phase we should, ideally, start by simulating scenarios witnessing errors (counterexamples). Of course, to know beforehand the set of such scenarios is not feasible. In this paper we show how to select scenarios so as to minimise the Worst Case Expected Verification Tim
Sparsity-Sensitive Finite Abstraction
Abstraction of a continuous-space model into a finite state and input
dynamical model is a key step in formal controller synthesis tools. To date,
these software tools have been limited to systems of modest size (typically
6 dimensions) because the abstraction procedure suffers from an
exponential runtime with respect to the sum of state and input dimensions. We
present a simple modification to the abstraction algorithm that dramatically
reduces the computation time for systems exhibiting a sparse interconnection
structure. This modified procedure recovers the same abstraction as the one
computed by a brute force algorithm that disregards the sparsity. Examples
highlight speed-ups from existing benchmarks in the literature, synthesis of a
safety supervisory controller for a 12-dimensional and abstraction of a
51-dimensional vehicular traffic network
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