Joy Lin, MathWorks
Companies must both deliver high-quality systems to the market today and develop exciting innovations for tomorrow, all while controlling costs. To accomplish this paradoxical challenge, innovative companies have adopted Model-Based Design over traditional development methods. Model-Based Design starts with a set of requirements that are used to develop executable specifications in the form of models rather than textual specifications. Engineers use these models to clarify requirements and specifications, quickly evaluate design alternatives through simulation, and then automatically generate production code. In this session, we present a set of case studies that demonstrate how leading companies in the aerospace and defense industry meet market challenges to win new contracts and develop the next generation of innovations. Their return on investment goes beyond the achieved improvement in quality and time to market; it extends to the additional capacity made available to meet their next design challenge.
Craig Borghesani, MathWorks
System and power engineers face many challenges, including validating power consumption requirements and modeling power distribution systems that include degradation effects of power source and storage devices. This session focuses on the use of Simulink and its suite of physical modeling libraries for the design and analysis of electrical power systems for spacecraft. We demonstrate how you can use dynamic simulation to overcome these challenges and explore how MathWorks tools can help you in every step of the design process.
David King, Bell Helicopter
With the maiden flight of the Bell/Agusta 609 Tiltrotor in 2003, a revolution in commercial air transport was launched. Like a helicopter, the BA609 takes off and lands vertically. Once aloft, the nine-passenger aircraft flies like a turboprop—at nearly twice the speed of a helicopter—allowing it to satisfy a wide range of missions, from executive transport to oil exploration, search and rescue, and emergency medical services. Approximately 300 flight hours have been logged on the first two prototypes during parallel testing at Bell’s flight test facility in Texas and Agusta’s facility in Italy. Pilots have probed handling qualities and flight loads at all corners of the flight envelope including speeds of 310 knots, altitudes up to 25,000 feet, maximum gross weight of 16800 lbs, and maneuvers to +3 g’s and -1 g’s, proving that the BA609 is one of the world’s most versatile and potentially useful commercial aircraft.
The BA609 program was confronted with numerous challenges associated with developing an innovative aircraft. This session presents the BA609 as a case study for integrating Model-Based Design and simulation into a large-scale systems engineering process. Starting with a basic set of customer needs and wants, the BA609 development team used frequent and extensive simulations to develop an integrated air vehicle with a fly-by-wire flight control system that has performed well in flight test demonstrations. An iterative design approach—using MATLAB, Simulink, Real-Time Workshop®, and Control Systems Toolbox™—yielded a set of flight control laws for low-workload control along with active structural loads protection.
Richard Ruff, MathWorks
MathWorks products enable Model-Based Design, which improves engineering productivity on safety-critical systems, including those that must meet DO-178B certification standards. This session presents a workflow using MathWorks tools for requirements validation, algorithm design, traceability, code generation, test generation, formal methods verification, and processor in-the-loop testing. Interfaces to requirements management and configuration management tools are also presented.
Development of real-time, algorithm-intensive software is costly and oftentimes drives a program's critical path schedule. Many programs across Raytheon are looking to incorporate Model-Driven Development (MDD) concepts during the development of these programs to increase software productivity and reduce cost and risk.
A migration to a joint systems-software (e.g., "SysWare") engineering product development cycle utilizing common models, task sharing, and well-defined handoffs between the functional disciplines is required. SysWare engineering requires the software engineers to get involved at the earliest stages of algorithm design and the systems engineers to be constantly aware of the final product (i.e., the production source code) and their impact on it.
This session discusses the rationale and reasoning behind the various products generated to support a SysWare engineering environment:
- Modeling Standard Handbook that provides guidance to the algorithm designer to facilitate automatic generation of production-quality code directly from the model
- SE-SW Workflow Diagram/Checklist that is tailored for specific programs, based on the varying expertise of the SE and SW engineers involved
- Configuration Management Guidance for model artifacts to ensure the ability of each functional discipline to update shared model elements
- Recommended approach for implementing a reference software architecture into a Simulink algorithm model to allow automatic code generation
Marc Barberis, MathWorks
This session demonstrates how to model the effects an electronic interferer on an end-to-end communication system using MATLAB and Simulink. The example shows how to interactively select different interfering signal types, power levels, and locations and then see the effects on system-level metrics such as bit error rate. It also shows how to include mitigation algorithms such as adaptive beam-forming.
Corinne Ilvedson, Insitu
Simulation plays a key role throughout the product life cycle at Insitu. As a result, the ScanEagle and Integrator simulations must satisfy the needs of a diverse customer set that includes product designers, software developers, system testers, incident investigators, UAS instructors, and UAS field operators. Aerospace companies typically address their simulation needs using their own proprietary framework that has been developed and vetted over several decades. However, as a small startup company, Insitu did not have a simulation legacy to leverage.
Not wanting to reinvent the wheel, Insitu chose to use MathWorks tools to create a modular and flexible simulation framework that enables rapid development of new features, is easily extendable and maintained, and meets the needs of the various simulation customers. The resulting simulation capability is powerful and versatile for software development, debugging, and test and yet user-friendly for UAS operators who don't have an engineering background. This session discusses the architectural approach used to develop Insitu's simulation tool, which is based on MathWorks products.
Marc Barberis, MathWorks
In this master class, we showcase new capabilities of MathWorks products you can use to generate C code from your Embedded MATLAB® code. You will learn about these capabilities by going through an example for the design of a video processing system. Through demonstrations, you will learn how to:
- Create and modify your MATLAB algorithms to comply with the Embedded MATLAB language subset
- Generate C code from your Embedded MATLAB code directly from the MATLAB desktop
- Call your Embedded MATLAB code as a new block within Simulink to integrate and simulate your algorithm as part of a larger system model
Dave Forstot, MathWorks
In this master class, we show how you can use MATLAB to solve the unique challenges posed by telemetry data analysis. Specifically, you will learn how you can use MATLAB and related toolboxes to:
- Import poorly formatted data
- Manage data in the MATLAB workspace using advanced techniques
- Quickly visualize data interactively and programmatically
- Evaluate techniques for dealing with missing or poorly sampled data
- Automate importing, analysis, and visualization of data
- Develop a user interface for others to utilize analysis and visualization routines