Accurate physics modeling in a Game-engine (Offshore)

Staff Mentor:

prof. J. Hellendoorn

Other Mentor(s):

Ir. Maarten Vaandrager, JB Systems


Learning and adaptive control; Data driven and fault tolerant control; Machine learning; System identification


The offshore industry is continuously pushing engineering to its limits. Every subsequent project typically needs to be larger, heavier, faster or deeper than the previous. These are high cost, high stakes and high risk projects.

JB Systems provides the control system for customer critical processes such as pipe lay equipment, dredging, stone dumping and crew transfer systems. While the continuous push for innovation makes the offshore industry a challenging and fun industry to work in, the high stakes and high risk of the projects is also a serious reason for concern for our customers. The risks range from costly technical delays during commissioning to catastrophic damage and even loss of life.

To mitigate these risks we can perform simulations. The simulation is used to validate the concept, debug the software and allow our customers to train their process operators in a zero risk environment.

JB Systems has built a number of simulators comprising of the PLC’s that run the automation software, the human machine interface (HMI), a 3d visualization made in a game engine and physics (multi body dynamics, hydraulics, electronics and hydrodynamics) done in Simulink. These components and programs are connected together to form ‘the simulator’.

Although Simulink is used for physics simulation, Unity also has extensive build-in physics functionality such as rigid body dynamics, collision detection, friction models etc. However these physics models are designed for performance, not accuracy. For some aspects these models are sufficient, for other aspects better accuracy is required.

The question is: can game engines achieve physics accuracy comparable to Simulink? If so, this would allow a large reduction of the complexity of the simulator as processes can be calculated and visualized within the same 3d environment without the need of coupling different programs.


- Research literature on ODE solvers, the methods used in Simulink and game engines and the differences between the two.

- Demonstrate that a dynamic process can be simulated within a game engine with the same accuracy as Simulink.

- Identify what the strengths and weaknesses are of Simulink vs the game engine and provide recommendations.

Desription from JB Systems

© Copyright Delft Center for Systems and Control, Delft University of Technology, 2017.