scholarly journals Grey Estimator-Based Tracking Controller Applied to Swarm Robot Formation

Axioms ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 298
Author(s):  
Yu-Ting Chen ◽  
Chian-Song Chiu ◽  
Ya-Ting Lee
Keyword(s):  
Mobile Robots ◽  
Trajectory Tracking ◽  
Feedback Linearization ◽  
Controller Design ◽  
Linear Feedback ◽  
Swarm Robots ◽  
Feedback Compensation ◽  
Tracking Controller ◽  
Multi Agent ◽  
Swarm Robot

Mobile robots are widely used in many applications, while various types of mobile robots and their control researches have been proposed in literature. Since swarm robots have higher flexibility and capacity for teamwork, this paper presents a grey estimator-based tracking controller for formation trajectory tracking of swarm robots. First, wheel-type mobile robots are used and modeled for the controller design. Then, a grey dynamic estimator is developed to estimate the environmental disturbance and model uncertainty for linear feedback compensation. As a result, the asymptotic trajectory tracking is assured, so that the application on the swarm robot formation is achieved for a multi-agent system. The computational complexity is slightly reduced by the design. Finally, in order to verify the reliability of swarm robot formation, several types of formation are maintained by the grey estimator-based feedback linearization controller.

Trajectory Tracking Controller Design for Mobile Robots with Bounded Input

2013 ◽  
Vol 427-429 ◽  
pp. 1145-1149
Author(s):  
Juan Wang ◽  
Xiu Feng Zhang
Keyword(s):  
Mobile Robots ◽  
Trajectory Tracking ◽  
Controller Design ◽  
Control Law ◽  
Robust Tracking ◽  
Wheeled Mobile Robots ◽  
Tracking Controller ◽  
Actuator Constraints ◽  
Trajectory Tracking Controller ◽  
Bounded Input

In this paper, the robust trajectory tracking problem has been addressed for nonholonomic wheeled mobile robots with dynamic uncertainties, disturbance and actuator constraints. control theory, LMI theory and principle of MPC are utilized to design robust tracking controller. Simulation is performed to highlight the effectiveness of the proposed control law.

A trajectory tracking controller with dynamic gains for mobile robots

2011 ◽  
Author(s):  
Cassius Z. Resende ◽  
F. Espinosa ◽  
I. Bravo ◽  
Mario Sarcinelli-Filho ◽  
Teodiano F. Bastos-Filho
Keyword(s):  
Mobile Robots ◽  
Trajectory Tracking ◽  
Tracking Controller ◽  
Trajectory Tracking Controller

scholarly journals A COMPARISON OF LYAPUNOV AND FUZZY APPROACHES TO TRACKING CONTROLLER DESIGN

2020 ◽  
Vol 1 (2) ◽  
pp. 54-57
Author(s):  
Tan- Sang Le ◽  
Le Hong Hieu
Keyword(s):  
Mobile Robots ◽  
Lyapunov Stability ◽  
Tracking Control ◽  
Controller Design ◽  
Final Goal ◽  
Tracking Controller

There are numerous types of locomotion of mobile robots. Therein, the most widespread type of locomotion is motion using wheels. The task of robot is transport themselves from place to place. And tracking control is always an important problem to appply robots in practice. The robot has to reach the final goal by following a referenced trajectory. The paper proposes two methods based on the lyapunov stability standard and fuzzy law. Then, we simulate the algorithms to evaluate the results.

A self-tuning trajectory tracking controller for wheeled mobile robots

2019 ◽  
Vol 46 (6) ◽  
pp. 828-838 ◽  
Author(s):  
Pouya Panahandeh ◽  
Khalil Alipour ◽  
Bahram Tarvirdizadeh ◽  
Alireza Hadi
Keyword(s):  
Neural Networks ◽  
Convergence Rate ◽  
Mobile Robots ◽  
Trajectory Tracking ◽  
Suggested Method ◽  
Wheeled Mobile Robots ◽  
Trajectory Tracking Control ◽  
Content Type ◽  
Tracking Controller ◽  
Trajectory Tracking Controller

Purpose Trajectory tracking is a common problem in the field of mobile robots which has attracted a lot of attention in the past two decades. Therefore, besides the search for new controllers to achieve a better performance, improvement and optimization of existing control rules are necessary. Trajectory tracking control laws usually contain constant gains which affect greatly the robot’s performance. Design/methodology/approach In this paper, a method based on neural networks is introduced to automatically upgrade the gains of a well-known trajectory tracking controller of wheeled mobile robots. The suggested method speeds up the convergence rate of the main controller. Findings Simulations and experiments are performed to assess the ability of the suggested scheme. The obtained results show the effectiveness of the proposed method. Originality/value In this paper, a method based on neural networks is introduced to automatically upgrade the gains of a well-known trajectory tracking controller of wheeled mobile robots. The suggested method speeds up the convergence rate of the main controller.

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