Trajectory tracking control of nonholonomic mobile robots by Backstepping

Author(s):  
Lei Cheng ◽  
Lei Cao ◽  
Huai-yu Wu ◽  
Quan-min Zhu ◽  
Wen-xia Xu ◽  
...  
Author(s):  
Meiying Ou ◽  
Haibin Sun ◽  
Zhenxing Zhang ◽  
Lingchun Li

This paper investigates the fixed-time trajectory tracking control for a group of nonholonomic mobile robots, where the desired trajectory is generated by a virtual leader, the leader’s information is available to only a subset of the followers, and the followers are assumed to have only local interaction. According to fixed-time control theory and adding a power integrator technique, distributed fixed-time tracking controllers are developed for each robot such that all states of each robot can reach the desired value in a fixed time. Moreover, the settling time is independent of the system initial conditions and only determined by the controller parameters. Simulation results illustrate and verify the effectiveness of the proposed schemes.


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.


Robotica ◽  
2018 ◽  
Vol 36 (5) ◽  
pp. 676-696 ◽  
Author(s):  
Tiago P. Nascimento ◽  
Carlos E. T. Dórea ◽  
Luiz Marcos G. Gonçalves

SUMMARYModel predictive control (MPC) theory has gained attention with the recent increase in the processing power of computers that are now able to perform the needed calculations for this technique. This kind of control algorithms can achieve better results in trajectory tracking control of mobile robots than classical control approaches. In this paper, we present a review of recent developments in trajectory tracking control of mobile robot systems using model predictive control theory, especially when nonholonomicity is present. Furthermore, we point out the growth of the related research starting with the boom of mobile robotics in the 90s and discuss reported field applications of the described control problem. The objective of this paper is to provide a unified and accessible presentation, placing the classical model, problem formulations and approaches into a proper context and to become a starting point for researchers who are initiating their endeavors in linear/nonlinear MPC applied to nonholonomic mobile robots. Finally, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works, including our contributions to state-of-the-art.


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