Deep Learning implemented to Adaptive Predictive Control in UAVs

Artificial intelligence (IA) also comes related with the term Deep Learning. The latest success in this field has created a huge expectation in the science community in order to solve tasks using sensor’s compiled raw data configured specially for this objective. This technology has a presence in a wide range of industries like automobiles, which has very similar modules as professional UAVs autopilots.

What is Deep Learning or Automatic learning?

Deep Learning is a combination of algorithms of automatic learning which deep learning attempts to model high-level abstractions in data using no-lineal multiple composed architectures.

In UAVs (Unmanned Aerial Vehicles) is currently applied Deep Learning by a function called Control Adaptive. In general, this kind of predictive capacitation in professional drones permits the UAV to predict possible changes in the environment or inside itself. In this order, the platform can maintain an optimal level and control-flight all over his path. That’s why Embention invests day-by-day enhancing I+D to make this Deep Learning process more advanced as possible at Veronte Autopilot.


Adaptive Predictive Control as a high-reliability flight’s highlight

Adaptive Control is a system which allows controlling the structure according to variable parameters or unknown. Contrary to non-adaptive controls, which maintain fixed control parameters throughout the operation. This method focuses on control changes, setting specific parameters in consonance with variations in the platform and environment.

Adaptive control is essential in UAVs, allowing the controller to be set to automatically adapt to changing flight conditions. An example of this is the one applied for weight compensation, where during the flight of an airship, its mass decreases as a consequence of fuel consumption.

To perform this procedure, can be to apply a conversion formula that automatically regulates the controller in line to certain system variables or to integrate plant auto-identification algorithms. In this case, the system adjusts the controller itself according to the status of the autopilot-controlled system.

Deep Learning neural network schema

UAVs Control Adaptive applications

This type of controlling has wide applications in professional drones field, whereby we can highlight: aircraft of big dimensions, aircraft in charge of logistical works or liquid dispensation. Where the payload is considerable or the platform’s mass by itself. Also is incorporated in high-speed systems, failproof, tethered drones, etc. In which is required the existence of the Control Adaptive system as the main value to the drone to works properly.

The Veronte Autopilot not only incorporates the function of Adaptive Control, but also works and invests constantly in developing a predictive system to be able to carry out an advanced control of any aircraft, regardless of its conditions, mass, payload, and typology.