With the advent of faster computer processors and better optimization algorithms,
Model Predictive Control (MPC) systems are more readily used for real-time applications.
This research focuses on the application of MPC to trajectory generation of autonomous
vehicles in an online manner. The operating environment is assumed to be unknown with
various different types of obstacles. Models of simplified 2-D dynamics of the vehicle are
developed, discretized and validated against a nonlinear CarSim vehicle model. The developed
model is then used to predict future states of the vehicle. The relationship of the
weight transfer to the tire slip angle is investigated. The optimal trajectory tracking problem
is formulated in terms of a cost function minimization with constraints. Initially, a gradient
descent method is used to minimize the cost function. A MATLAB based MPC controller
is developed and interfaced with CarSim in order to test the controller on a vehicle operating
in a realistic environment. The effects of varying MPC look-ahead horizon lengths on
the computation time, simulation cost and the tracking performance are also investigated.
Simulation results show that the new MPC controller provides satisfactory online obstacle
avoidance and tracking performance. Also, a trajectory tracking criterion with goal point information
is found to be superior to traditional trajectory tracking methods since they avoid
causing the vehicle to retreat once a large obstacle is detected on the desired path. It is further
demonstrated that at a controller frequency of 20Hz, the implementation is real-time
implementable only at shorter horizon lengths. / UOIT
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OOSHDU.10155/206 |
| Date | 01 November 2011 |
| Creators | Abbas, Muhammad Awais |
| Contributors | Eklund, Mikael, Milman, Ruth |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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