Accelerating Complex System Development with MATLAB and Simulink
Kongsberg, Norway
| Venue | Start Date | End Date |
|---|---|---|
| Home Hotel 1624, Sildetomta 2-4, 3612 Kongsberg, Norway | 30 Sep 2026, 08:30 CEST | 30 Sep 2026, 13:30 CEST |
Overview
Developing complex engineered systems requires teams to balance performance, safety, verification, and increasing system complexity. Join MathWorks for this in person seminar to explore how modelling, simulation, and Model-Based Design can help accelerate development from early system architecture through to validation and testing.
Through practical examples and demonstrations, you'll see how MATLAB and Simulink support systems engineering, safety analysis, control design, virtual validation, and emerging AI-assisted engineering workflows.
Highlights
- Explore the latest approaches to fault modelling and safety analysis within a Model-Based Systems Engineering workflow
- Learn how high-fidelity system simulation supports design exploration, virtual validation, and real-time testing
- Discover how Agentic AI can accelerate engineering workflows while maintaining traceability and engineering rigour
- See practical examples from real Model-Based Design applications
Who Should Attend
System engineer, Control engineer, Simulation engineer
Agenda
| Time | Title |
08.30 |
Registration |
9.40 – 10.00 |
Welcome and Introduction |
10.00 – 10.45 |
Simulation-Driven Safety Analysis in Model-Based Systems Engineering This presentation showcases how MathWorks Model-Based Systems Engineering (MBSE) workflow enhances safety analyses, including the industry-standard Failure Mode and Effects Analysis (FMEA). Discover how advanced fault simulation capabilities in MATLAB and Simulink enable systematic safety analyses to design safe systems. Learn the strategies for establishing a comprehensive safety analysis framework that integrates seamlessly into the overall system design process. |
11.00 – 11.45 |
System Simulation for Design Exploration and Virtual Validation System simulation plays an important role throughout the development lifecycle, supporting design decisions, control development, system integration, and validation activities. Effective design exploration and verification require models that accurately represent the dynamics of interest while remaining computationally efficient for large-scale studies, optimization, and hardware-in-the-loop (HIL) testing. This session discusses approaches for developing and managing simulation models of varying fidelity, enabling engineers to balance accuracy and performance while supporting virtual testing and validation before physical systems are available. |
12.45 - 13.30 |
Design and Deploy Control Systems with Agentic AI and Model-Based Design Agentic AI is transforming how engineers develop complex control systems by accelerating tasks such as model creation, controller implementation, and test development. However, engineering organizations still require rigorous design processes to ensure performance, safety, and traceability. This session explores how Agentic AI can be integrated into a Model-Based Design workflow, enabling engineers to collaborate with AI while maintaining full oversight of the development process |
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