Leader-Follower Approach using Full-State Linearization via Dynamic Feedback

Abstract

In this work, the leader-follower control problem is solved by using Full-state linearization via dynamic feedback. This approach has certain advantages over the well known input-output linearization such as no relative point selection, simple extension to n-robots formation and representation of all dynamics incase of Car-Like Robot model. Simulation results verify the validity and limitation of these controllers by Matlab. The new 3-D robot simulator Gazebo with robot server Player is also used to verify the results.

A guidance law for UAV autonomous aerial refueling based on the iterative computation method

“…In Ref. 17, a full-state linearization via a dynamic feedback controller is designed for controlling two robots in a leader-follower configuration. In Ref.…”

Finite‐time formation control of multiple nonholonomic mobile robots

“…Compared with the elegant results in the linear case, the problem of formation control for multiple nonholonomic mobile robots is not a trivial one because of mobile robots’ nonlinear dynamics and nonholonomic constraints. In , the formation control problem was discussed on the basis of the methods of leader–follower and dynamic feedback linearization. In , the backstepping design scheme is employed to solve the problem of formation control for multiple nonholonomic chained‐form systems.…”

“…The problem of formation control for a group of mobile robots is to assign a geometric structure or pattern to the group, such that the robots attain this formation and keep it over time. Many formation control strategies have been proposed, for example, behavior-based [1][2][3], virtual structure-based [4][5][6], leader-follower-based [7][8][9][10], and graph theory-based controls [11][12][13].…”

Decentralized hybrid formation control of Unmanned Aerial Vehicles

“…For instance, for reaching the formation, methods such as MILP programming, navigation function, and potential field have been developed [5], [6], [7], [8]. Keeping the formation can be seen as a standard control problem in which the system's actual position has slightly deviated from the desired position [9], [10], [11]. Finally, in [12], [13], [14], [15], different scenarios for collision avoidance have been introduced using geometry approaches, predictive control, probabilistic methods, and invariant sets.…”