"Formation control of mobile robots and unmanned aerial vehicles" by Travis Alan Dierks
 

Doctoral Dissertations

Keywords and Phrases

Leader-follower formation control

Abstract

"In this dissertation, the nonlinear control of nonholonomic mobile robot formations and unmanned aerial vehicle (UAV) formations is undertaken and presented in six papers. In the first paper, an asymptotically stable combined kinematic/torque control law is developed for leader-follower based formation control of mobile robots using backstepping. A neural network (NN) is introduced along with robust integral of the sign of the error (RISE) feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. Subsequently, in the second paper, a novel NN observer is designed to estimate the linear and angular velocities of both the follower and its leader robot and a NN output feedback control law is developed. On the other hand, in the third paper, a NN-based output feedback control law is presented for the control of an underactuated quad rotor UAV, and a NN virtual control input scheme is proposed which allows all six degrees of freedom to be controlled using only four control inputs. The results of this paper are extended to include the control of quadrotor UAV formations, and a novel three-dimensional leader-follower framework is proposed in the fourth paper. Next, in the fifth paper, the discrete-time nonlinear optimal control is undertaken using two online approximators (OLA's) to solve the infinite horizon Hamilton-Jacobi-Bellman (HJB) equation forward-in-time to achieve nearly optimal regulation and tracking control. In contrast, paper six utilizes a single OLA to solve the infinite horizon HJB and Hamilton-Jacobi-Isaacs (HJI) equations forward-intime for the near optimal regulation and tracking control of continuous affine nonlinear systems. The effectiveness of the optimal tracking controllers proposed in the fifth and sixth papers are then demonstrated using nonholonomic mobile robot formation control"--Abstract, page iv.

Advisor(s)

Sarangapani, Jagannathan, 1965-

Committee Member(s)

Balakrishnan, S. N.
Wunsch, Donald C.
Erickson, Kelvin T.
Dagli, Cihan H., 1949-

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Electrical Engineering

Sponsor(s)

National Science Foundation (U.S.)

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2009

Journal article titles appearing in thesis/dissertation

  • Neural network control of mobile robot formations using rise feedback
  • Neural network output feedback control of robot formations
  • Output feedback control of a quadrotor UAV using neural networks
  • Leader-follower formation control of multiple quadrotor unmanned aerial vehicles using neural networks
  • Optimal control of affine nonlinear discrete-time systems with unknown internal dynamics using online approximators
  • Optimal control of affine nonlinear continuous-time systems using an online approximator

Pagination

xiv, 328 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2009 Travis Dierks, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Subject Headings

Lyapunov stabilityMobile robots -- ProgrammingNeural networks (Computer science)Nonlinear control theory

Thesis Number

T 9553

Print OCLC #

746011089

Electronic OCLC #

497837428

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