Title

Discrete-time Optimal Control of Nonholonomic Mobile Robot Formations Using Linearly Parameterized Neural Networks

Abstract

In this paper, the infinite horizon optimal tracking control problem is solved online and forward-in-time for leader-follower based formation control of nonholonomic mobile robots. Using the backstepping approach and the kinematic controller developed in our previous work, the dynamical controller inputs for the robots are approximated from nonlinear optimal control techniques to track the designed control velocities. The proposed adaptive dynamic programming approach uses neural networks (NNs) to solve the optimal formation control problem in discrete-time in the presence of unknown internal dynamics and a known control coefficient matrix. All NNs are tuned online using novel weight update laws, and the stability of the entire formation is demonstrated using Lyapunov methods. Numerical simulations are also provided to demonstrate the effectiveness of the proposed approach.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Formation Control; Hamilton-Jacobi-Bellman; Nonholonomic Mobile Robot; Nonlinear Optimal Control

Library of Congress Subject Headings

Lyapunov stability

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2011 ACTA press, All rights reserved.


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