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Model predictive control of wheeled mobile robots

The control of nonholonomic wheeled mobile robots (WMRs) has gained a lot of attention
in the field of robotics over the past few decades as WMRs provide an increased range of
motion resulting in a larger workspace. This research focuses on the application of Model
Predictive Control (MPC) for real-time trajectory tracking of a nonholonomic WMR. MPC
is a control strategy in which the control law is designed based on optimizing a cost function.
The input and output constraints that may arise in practical situations can be directly
incorporated into the control system using MPC. Computation time is the biggest hurdle in
adapting MPC strategies for trajectory tracking. This research applies a non-feasible active
set MPC algorithm developed in [1] which is faster than the traditional active set methods
(ASMs). A discrete-time linear model of a general WMR is used for the simulation. MATLAB
simulations are performed for tracking circular as well as square trajectories using
the discretized WMR model and the non-feasible ASM (NF-ASM). The performance of
NF-ASM is compared to two other well-known traditional algorithms, i.e. Fletcher’s ASM
and MATLAB’s Quadratic Programming algorithm. It is shown that, although all these
algorithms are capable of providing satisfactory trajectory tracking performance, NF-ASM
is a better choice in terms of the simulation time and required number of iterations for realtime
trajectory tracking of any type as long as the constraints on the inputs stay active for a
long period during the simulation. / UOIT

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OOSHDU.10155/136
Date01 December 2010
CreatorsChowdhry, Haris
ContributorsMilman, Ruth
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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