Intelligent control engineering

We use innovative methods from the fields of control engineering and artificial intelligence to control complex processes.

To control complex processes intelligently, we develop solutions at the interface between classic control engineering and artificial intelligence. A classic method from control engineering is model-based predictive control. Here, a simulation model of the process is used to calculate into the future and intervenes in the closed control loop only if this change is safe and will lead to an improvement of the operating point in the long run.

Reinforcement learning is a method from the field of artificial intelligence. In this case, the regulator is automatically learning through interaction with the system to be regulated, which leads to very innovative regulators

We will find the best solution for you

We utilize state-of-the-art hardware and algorithms to solve computing-intensive regulating problems in real-time. We monitor the latest developments in the field of deep reinforcement learning by attending international conferences and studying scientific publications to offer you the best solutions at all times.

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