Modeling & simulation
Often used as synonyms, we treat modeling and simulation as individual and equally important concepts. Modeling is understood as the purposeful abstraction of reality. Model implementation and execution over time is known as simulation.
Selecting the proper tools or building high-performing implementations, or applying advanced concepts like co-simulation and hardware-in-the-loop: we help at any phase of your project.
We have extensive and proven experience with modeling and simulation, in a variety of domains, for a variety of purposes. We develop your models from scratch or support your project team to overcome specific challenges.
Modeling objectives & use cases
The modeling discipline aims to optimize designs from the start, preventing costly and time-consuming iterations. Especially valuable for optimizing dynamic behavior and testing conditions that are impractical, costly or perilous to reproduce in real-world. Understand, optimize and thoroughly test your designs at the earliest stage. Improve your product quality and typically reduce development time by 50% or more.
Observe dynamic system behavior over time with simulation, at the required level of detail. Linear or non-linear dynamics, in continuous or discrete time domain. Open-loop or closed-loop, combined with control system models. Plenty of use cases to understand and optimize system dynamics from the start.
Many experiments are perilous in real-world. Consider new vehicle cruise-control algorithms: you rather discover software flaws in simulation instead of on the road. Simulate impact and gain insights in behavior under extreme conditions, free of real-world risk.
Saving time and money
Waiting for time slots on a test-bench, costs for procuring prototypes, hardware iterations: all consuming both time and money. Instead, mature your designs in simulation, before entering real-world. System integration? Use simulation to run tests overnight, for each new software update. Find and fix bugs early on.
Animate systems in 2D/3D and use models in a serious-gaming setting to train your operators. Let concepts be more easily verified, communicated and understood. Before you enter production. Monitor and display dynamics that you cannot easily capture in real-world, in absence of sensor capabilities. Take a good look 'inside', to truly get to know your system.
Failure mode effect analysis (FMEA)
What happens if sensors fail? What is the impact of system overloads? Is your system robust against emergency stops or power outages? Do fall-back strategies work? Perform dedicated FMEA analysis in simulation to methodically validate robustness.
Enable model-based control design
Engaging in control design? Model both your plant and your controller. Discover what works and what doesn't. Is your algorithm stable under all conditions? Are performance indicators met? Integrate plant models as state-estimators, where needed. Or take the next leap: generate production code from your controls model.
Move your design tasks from lab-and-field to the laptop: capture mathematical relationships at play in your system and simulate a wide range of conditions. Discover dynamic behavior and share insights with your team. In other words: get a grip, from the start.
Engage in physical modeling where possible. Rapid-prototype your controls directly on your system. Verify software with Hardware-in-the-Loop. Discover the power of simulation, we gladly help you up to speed.
Physical modeling & advanced concepts
Implement your mathematical model directly in block systems, or let SIMULINK take care of math - where possible - by using its Physical Modeling libraries: modules are readily available for multiple domains such as mechanics, hydraulics and electronics. Or combine the two paradigms in hybrid models. Our experience entails both mathematical and physical modeling: let us explore your system and deliver optimal, high-performance simulation platforms.
Certain projects require pioneering and advanced simulation concepts. We gladly accept the challenge. As MathWorks partners, we know how to liaise with SIMULINK developers, getting the most out of your simulation environment.
Next to serving design purposes, models are widely used for control design. Interface your simulation with hardware platforms for control prototyping and production Control-Unit (embedded software) testing. The two major simulation modes that include hardware:
- Rapid Control Prototyping (RCP)
- Hardware in the Loop (HIL)
In RCP simulation, your control system model is deployed on a prototyping controller (like dSpace, xPC target), allowing you to validate and optimize your strategies on actual hardware. Tackle performance, robustness and calibration challenges right from the start.
Need to validate production control-units and their software? Perform HIL simulation and put your controller through its paces: testing a wide range of conditions, both success-scenarios and failure-modes like (simulated) sensor failures.