Modeling and simulation of complex/dynamic systems


  • Mathematical modeling and identification of interrelationships within a system
  • System modeling and simulation with Matlab / Simulink and other toolboxes
  • System design and optimization based on simulation results
  • Design and tuning of control systems (control systems engineering)
  • Requirements verification and design validation
  • Mathematical model verification and validation, correlation with measurements


Simple systems are intuitive to understand and their development is relatively straightforward. Nowadays, however, most newly developed systems are far from simple: They are often highly complex and interlinked structures of multiple dynamic subsystems showing a high degree of multidisciplinary relationships between them. Such systems can only be fully understood analytically.

In this case the key to a cost and time efficient development lies with the proper modeling of the complete system, so that all relevant aspects are fully and accurately described mathematically, using conventional and differential equations and an appropriate set of parameters, in a single coherent model. The level of detail hereby required is optimized according to the specifics of the project.

Once finalized and validated, this model can be used to quickly obtain large amount of information about the behavior of the system under all possible operating conditions, first and foremost to verify the fulfillment of the specified requirements.
Sensibility studies can also be rapidly performed to understand the consequences of changes within the system so that different configurations and design choices can be evaluated.
The knowledge gained from this data and the quick evaluation of design changes allows faster design iterations and rapid optimization of the entire system. This is one of the key factors to success in the early stages of a new project.

The suitability of component candidates can be verified as well and system cost can be estimated with a higher degree of precision and confidence. Such a model is therefore an invaluable tool not only for engineers, but also for managers, as it enables them to make strategic decisions based on sound feasibility, risk and cost analyses.

Furthermore, the model can also be used to assess the feasibility and estimate the cost of product customizations and to efficiently react to component obsolescence, bringing benefits also at later stages of the product lifecycle.

This methodology is called model-based design or model-based development and is part of the broader concept of virtual prototyping. It is a proven and efficient method and is steadily gaining acceptance in the industry by many innovative and successful companies, which are facing increasingly difficult challenges in the development of more and more complex systems.
Model based design is an integral part of Industry 4.0 and a key factor to ensure that a company remains competitive and successful in the future.

In this field we have considerable know-how and years of successful experience from a variety of projects. We are therefore in the best position to advise you if, when and to which extent it is applicable to your development processes.


  • System modeling and simulation, subsystems interaction analysis (e.g. between mechanics, electronics and control system).
  • Feasibility studies
  • System design
  • Maintenance strategies
  • Identification of technical and economic risks, for sound standing and substantiated decision-making about investments and project strategy
  • Detailed, accurate and solid cost estimates. Cost-of-specification knowledge
  • Quick evaluation of customization requests, cost and time estimates
  • Fast and efficient response to component obsolescence
  • Tests and measurement data processing, live data display