Latest revision as of 11:52, 25 January 2021

Abstract

In this paper, a simulation framework based on the kinematic model for the multi agent robots using the leader-follower formation was presented. The design of feedback controllers for leader-follower formation using feedback linearization techniques was also presented. The follower robots derived their inputs based on the control inputs sent by the leader robot. The leader robot transmitted its control inputs to the follower using the Bluetooth piconet profile. The posture stabilization controllers using smooth time-varying, polar coordinates and dynamic feedback controller were simulated for the leader robot. For trajectory tracking, the reference trajectory was generated using the feedforward command controller. The multi agent nonholonomic robotic system was modeled using MATLAB/Simulink and the feedback strategies were simulated for a given set of reference trajectories. Based on the simulation results for the various trajectories, the following conclusions are made: ? For the leader robot, the full state linearized controller via dynamic feedback minimizes the mean of error more rapidly than the other feedback strategies. ? The full state linearized dynamic feedback controller for the leader robot achieves posture stabilization. ? The feedback strategies designed using cascaded systems theory and using linearization of corresponding error model fail to track the trajectory if the leader robot's starting point and the trajectory starting point is not the same (circular shaped trajectory).

Original document

The different versions of the original document can be found in:

• http://www.intechopen.com/articles/show/title/control_analysis_and_feedback_techniques_for_multi_agent_robots

• https://www.intechopen.com/citation-pdf-url/6106 under the license cc-by-nc-sa

• https://cdn.intechopen.com/pdfs/6106/InTech-Control_analysis_and_feedback_techniques_for_multi_agent_robots.pdf,

https://www.intechopen.com/books/multiagent_systems/control_analysis_and_feedback_techniques_for_multi_agent_robots,

http://cdn.intechweb.org/pdfs/6106.pdf,

https://academic.microsoft.com/#/detail/2336618889

• https://www.intechopen.com/download/pdf/6106,

http://dx.doi.org/10.5772/6597