Overall Objectives
Research Program
Application Domains
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

Plug&Play control for highly non-linear systems: Stability analysis of autonomous vehicles

Participants : Francisco Navas, Fawzi Nashashibi.

The final stage for automating a vehicle relies on the control algorithms. They are in charge of providing the proper behavior and performance to the vehicle, leading to provide fully automated capabilities. Controllability and stability of dynamic complex systems are the key aspects when it comes to design intelligent control algorithms for vehicles.

Nowadays, the problem is that control systems are “monolithic”. That means that a minor change in the system could require the entire redesign of the control system. It addresses a major challenge, a system able to adapt the control structure automatically when a change occurred.

An autonomous vehicle is built by combining a set-of-sensors and actuators together with sophisticated algorithms. Since sensors and actuators are prone to intermittent faults, the use of different sensors is better and more cost effective than duplicating the same sensor type. The problem is to deal with the different availability of each sensor/actuator and how the vehicle should react to these changes. Another possible modification is the change in vehicle dynamics over time; or difference in dynamics from one vehicle to another.

A methodology that improves the security of autonomous driving systems by providing a framework managing different dynamics and sensor/actuator setups should be carried out. New trends are proposing intelligent algorithms able to handle any unexpected circumstances as unpredicted uncertainties or even fully outages from sensors. This is the case of Plug & Play control, which is able to provide stability responses for autonomous vehicles under uncontrolled circumstances.

Here, the basis of Plug & Play control, Youla-Kucera parameterization, has been used to develop different applications within the autonomous driving field.