MATLAB and Simulink for Aerospace and Defense

Design, simulate, test, and deploy safety and mission critical systems

Aerospace and defense companies worldwide rely on MATLAB® and Simulink® across all technology readiness levels, from prototypes to their most important safety and mission critical systems. MATLAB and Simulink are used in major programs across all domains, such as the F-35 Joint Strike Fighter and Mars Exploration Rover, and accelerate research and development in areas like autonomous systems, hypersonics, advanced wireless systems, and hybridization and electrification of aircraft.

Digital engineering with Model-Based Design helps to reduce program risks (like performance, schedule, and integration) through early design simulation and code generation. Simulink for systems engineering also establish a digital thread, providing traceability between requirements, architecture, design, auto-generated code, and test artifacts. This ensures design completeness and eases change management of complex systems, all within the same environment.

During the “third wave” of artificial intelligence, domain experts are also using MATLAB and Simulink to develop AI solutions to make earlier predictions and improve decision making. MATLAB and Simulink allow teams to incorporate a variety of data sources and accelerate the implementation of machine learning, deep learning, and data science algorithms into their applications that can be deployed to hardware or the cloud.

“Model-Based Design gave us advanced visibility into the functional design of the system. We also completed requirements validation earlier than was previously possible and simulated multiple simultaneous component failures, so we know what will happen and have confidence that the control logic will manage it.”

Christopher Slack, Airbus

Systems Engineering

Systems engineering plays an increasingly crucial role in managing the complex requirements, architectures, and integration of multiple domains to ensure the delivery of systems with exceptional performance and safety. Simulink provides an easy-to-use architecture modeling and analysis environment that allows you to fully synchronize requirements with your Model-Based Design.

MATLAB and Simulink support digital engineering workflows by allowing users to:

View gallery (3 images)

Flight Controls and Engine Controls

Flight Controls and Engine Controls

Design and test safety-critical control systems through simulation before automatically generating code that is then integrated into the physical platform. Accelerate the development cycle by making it easier to design for different scenarios and platform configurations, test with hardware-in-the loop, and qualify control logic to safety standards like DO-178C – all within the same environment.

MATLAB and Simulink allow control engineers to:

Unmanned Aerial Vehicle Design

Unmanned aerial vehicle (UAV) engineers and scientists use MATLAB and Simulink to design and tune control systems and platform-agnostic intelligence, surveillance, and reconnaissance (ISR) mission algorithms, model real-world systems, then automatically generate and verify the code – all from one software environment.

MATLAB and Simulink enable engineers to:

Wireless Systems

Design, prototype, and test advanced algorithms, multi-function RF systems, and antenna arrays for the next generation of wireless communications (27:30), radar, and electronic warfare systems (35:28). With MATLAB and Simulink, research engineers can rapidly prove viability of new technology concepts, eliminate design problems early in the development cycle, and streamline design verification. With MATLAB and Simulink tools, engineers can:

Artificial Intelligence for Aerospace and Defense

MATLAB and Simulink provide a comprehensive platform for solving AI challenges from predictive maintenance to complex tasks like multimodal target identification. MATLAB empowers engineers even if they have limited AI experience. It helps teams better AI datasets, tackle integration challenges, reduce risk, and continuously test models in a system-wide context.

View image gallery (7 images)