Toward A Robust Model Predictive Controller Applied To Mobile Vehicle Trajectory Tracking Control

2011 ◽  
Vol 44 (1) ◽  
pp. 13552-13557 ◽  
Author(s):  
Mitra Bahadorian ◽  
Borislav Savkovic ◽  
Ray Eaton ◽  
Tim Hesketh
2018 ◽  
Vol 15 (1) ◽  
pp. 172988141876046 ◽  
Author(s):  
Tiago P Nascimento ◽  
Carlos Eduardo Trabuco Dórea ◽  
Luiz Marcos G Gonçalves

Trajectory tracking for autonomous vehicles is usually solved by designing control laws that make the vehicles track predetermined feasible trajectories based on the trajectory error. This type of approach suffers from the drawback that usually the vehicle dynamics exhibits complex nonlinear terms and significant uncertainties. Toward solving this problem, this work proposes a novel approach in trajectory tracking control for nonholonomic mobile robots. We use a nonlinear model predictive controller to track a given trajectory. The novelty is introduced by using a set of modifications in the robot model, cost function, and optimizer aiming to minimize the steady-state error rapidly. Results of simulations and experiments with real robots are presented and discussed verifying and validating the applicability of the proposed approach in nonholonomic mobile robots.


2018 ◽  
Vol 51 (31) ◽  
pp. 738-745 ◽  
Author(s):  
Yunxiao Li ◽  
Jun Ni ◽  
Jibin Hu ◽  
Bo Pan

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