A new model-free design for vehicle control and its validation through an advanced simulation platform
This work addresses vehicle control for advanced driving assistance systems, but it appears incremental as it builds on existing model-free control methods.
The paper tackles vehicle control by proposing a model-free approach using intelligent P and PD controllers for longitudinal and lateral motions, achieving best profile tracking without needing complex mathematical modeling, with validation through simulation using actual data from a Peugeot 406 and virtual data from the SiVIC/RTMaps platform.
A new model-free setting and the corresponding "intelligent" P and PD controllers are employed for the longitudinal and lateral motions of a vehicle. This new approach has been developed and used in order to ensure simultaneously a best profile tracking for the longitudinal and lateral behaviors. The longitudinal speed and the derivative of the lateral deviation, on one hand, the driving/braking torque and the steering angle, on the other hand, are respectively the output and the input variables. Let us emphasize that a "good" mathematical modeling, which is quite difficult, if not impossible to obtain, is not needed for such a design. An important part of this publication is focused on the presentation of simulation results with actual and virtual data. The actual data, used in Matlab as reference trajectories, have been obtained from a properly instrumented car (Peugeot 406). Other virtual sets of data have been generated through the interconnected platform SiVIC/RTMaps. It is a dedicated virtual simulation platform for prototyping and validation of advanced driving assistance systems. Keywords- Longitudinal and lateral vehicle control, model-free control, intelligent P controller (i-P controller), algebraic estimation, ADAS (Advanced Driving Assistance Systems).