Defence Business: The Evolution of Model-Based Design in Aerospace and Defence | ADM November 2012
By Matt Behr | Sydney | 7 January 2013
Model-Based
Design continues to grow within the aerospace and defence industries. This article
examines the reasons behind that growth and explores future trends in its
adoption. Particular focus is given to its use in the development of certified
systems and on large multi-organisation programs.
The development of aerospace and defence systems presents unique
challenges. The first challenge is managing their extraordinary scale and
complexity. Frequently, these projects are systems of systems, requiring
integration of disparate dedicated systems.
Next, low production volume means that nonrecurring engineering
costs are carefully scrutinised. One-time costs for research, design, and
development cannot be distributed over thousands or millions of units. Lastly,
testing these systems can be difficult, costly, and unsafe.
For example, commercial and military satellites cannot be fully
tested on the ground and conducting flight tests on new aircraft is both
expensive and hazardous.
Aerospace and defence organisations have long utilised modelling
and simulation to address these challenges. Simulation technologies, including
commercial tools such as Simulink, have evolved to support engineers throughout
the design, development, and testing cycles.
Early in the design cycle, simulations are used to understand
and analyse system behaviour. As the functional and performance requirements of
systems have evolved, so too have simulation and analysis capabilities.
Many organisations still use custom FORTRAN-based models in
their design processes. These custom environments, while effective for their
original task, can be difficult platforms on which to add modelling capabilities.
This dynamic has led the industry to turn to commercial-off-the-shelf (COTS)
simulation packages. An example of this evolution is the addition of discrete event
simulation to Simulink. NASA and TriVector Services recently used these
capabilities to analyse the impact of communication latencies on the Ares I
rocket.
In addition to providing design insights and facilitating
verification via simulation, modelling tools supporting code-generation allow
models to be reused throughout the project life cycle. Indeed, re-use is one of
the key advantages of Model-Based Design. Code generated from models is often
used in real-time hardware-in-the-loop testing.
By running models in real-time with hardware I/O, engineers can
compare the behaviour of the processors and hardware with the behaviour of the
simulated components.
Code generation also enables organisations to reuse algorithmic
models in production systems. Production code is generated automatically,
rather than re-implemented by hand, saving time and eliminating errors.
Compliance
burden
Having benefited from its utility in simulation, verification,
and production implementation, organisations are now looking to solve additional
challenges using Model-Based Design. Specifically, organisations are attempting
to ease the burden of compliance with industry-standards and enable integration
testing via simulation on multiorganisation programs.
High-integrity programs requiring compliance with industry
standards such as DO-178B present unique challenges. The increased burdens of
testing and artefact generation significantly increase cost. Model-Based Design
helps engineers achieve certification to safety standards by supporting requirements
traceability, verification, and documentation. These capabilities span multiple
design stages.
For example, requirements linked to model are inserted as
comments in generated code. Qualification kits, available for several
verification tools, can reduce the amount of manual review needed.
It is also increasingly common for organisations to adopt
Model-Based Design on large programs spanning multiple organisations. This
allows system-level performance to be assessed and integration issues to be
uncovered much earlier in the design process. When detailed models from
multiple organisations are combined, resulting models can contain hundreds of
thousands of blocks.
Modelling tools, such as Simulink, have evolved to meet these
challenges with improved support for large-scale modelling, including support
for composite models from other model files and support for signal buses.
Modelling standards are also becoming important for these
multi-organisation programs. Much like coding standards were adopted to
facilitate team development and sharing of source code, modelling standards are
being developed to support collaboration at the model level.
For example, the Orion Guidance, Navigation, and Control
(GN&C) MATLAB and Simulink Standards document describes the modelling standards
and guidelines that the Orion Crew Exploration Vehicle Flight Dynamics Team
used for GN&C algorithm development. The standards provide guidelines for
several aspects of the GN&C models, including stylistic rules, modelling
tool selection, and configuration settings, which affect model readability a
well as the generated code.
As Model-Based Design continues to evolve, it is enabling a
diverse and expanding group of leading organisations to improve efficiency,
increase reuse, and meet new challenges in developing modern aerospace and
defence systems.
Matt Behr, aerospace and defence industry manager,
MathWorks.