In the high-tech systems market, there is a continues drive to create machines with more accuracy, higher speeds, and disruptive technologies. This requires advanced control systems which use multiple sensor inputs and machine models to calculate the optimal steering of the actuators. Controllab provides these control systems.


The power system industry is shifting from centralized power generation to a grid with distributed energy resources, governed by smart control systems. Controllab is experienced in in the development and testing of these control systems. We help with the development of PLC code and have use our in-house developed toolset for the automatic testing of code using simulators. The diesel electric generator shown at the right is an example. On ships several of these generator sets have to be switched on and off to comply to the varying power demand. We have developed a real-time HIL-simulator to test the breaker circuits that have to switch off the generator in case of emergencies.


The automatic control of manipulators quickly becomes a nightmare, when high speeds, high accuracies or complex maneuvres are required. We have a lot of experience with robotic systems and can develop control systems that can meet these demands. We have ready-made software modules for:

  • Loop control for optimal tracking
  • Path planning, safe stopping, and obstacle avoidance
  • State machines for complex motions


Brushless DC (BLDC) motors are increasingly being used in all kind of equipment as a replacement for DC motors. This is because of their smooth running and long life. BLDC motors, however, need a sophisticated drive to run. Buying these drives custom-of-the-shelf can be very costly if you use these motors in large series. We provide solutions for DC and BLDC drives that can be integrated on embedded boards. This will save costs and minimize the foodprint. By adding modules for sensorless operation, self-calibration or condition monitoring we can bring your products to the next level of engineering.


We use model-based design to tackle complex machinery. Our simulation models combine both the control system and the physics of a machine. This mechatronic approach allows us to change the physics as well as the control system in quick iterations and come up with a design that will give optimal performance. In further stages of the design process, we re-use these models to test the implementation of the control system and facilitate the integration of the controller with physical parts of the system.

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