Artificial Intelligence and Control Systems – at the edge and in the cloud.

Stefan Ristevski, Control Systems Consultant at Combine, recently presented two papers at AIAA SciTech Forum. His research was on the topics “Scheduling Local Information Exchange in Linear Multiagent Systems Through an Event-Triggering Approach” and “Experimental Results of a Quadrotor UAV with a Model Reference Adaptive Controller in the Presence of Unmodeled Dynamics”.

Many people see machine learning (ML) systems as black boxes. Some believe these black boxes contain pure magic and have the power to solve any problem at hand. Others do not trust them at all, for what cannot be explained cannot be counted on. ML is not all so mysterious, though. Just like any other fields of engineering, ML relies on applied mathematics and applied science, and it uses scientific principles to design, build and test a system so that it becomes reliable and works efficiently in real time. Implementing a simple KNN classifier can be your first step to demystify ML.

This blog post may refer to aeronautical applications but Combine have been implementing a model-based approach in a wide variety of industries since 2005. The time saved in the development process is essential for some industries, while quick testing and better products are the main benefits for others.