Modeling and Predictive Control for Autonomous Vehicles
Andre Scolari
LaR - Robotics Lab., Federal University of Bahia Salvador - Bahia - Brazil
DEIB - 2A Room
March 9th, 2016
4.00 pm
Contact:
Andrea Bonarini
Research Line:
Artificial intelligence and robotics
LaR - Robotics Lab., Federal University of Bahia Salvador - Bahia - Brazil
DEIB - 2A Room
March 9th, 2016
4.00 pm
Contact:
Andrea Bonarini
Research Line:
Artificial intelligence and robotics
Abstract
The concept of prediction is ideal for applications with known future references. The main advantages of predictive control, which is more commonly used in industry, compared to classical control, are that it works better with multivariable problems, it considers constraints on the input and the state explicitly in its formulation, and it has better robustness characteristics adapting well to disturbances, nonlinearities, and modeling errors due to the moving horizon scheme.
This talk will be focused on the following topics:
This talk will be focused on the following topics:
- Modeling and Friction Estimation for Wheeled Mobile Robots
- Design of Model-Predictive Control With Friction Compensation
- Non-linear Model Predictive Control for Multi-Robot Systems.