Neural network output feedback control of robot formations

Authors:
Travis Dierks;Sarangapani Jagannathan
Affiliations:
University of Missouri-Rolla, Rolla, MO and The Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO;University of Missouri-Rolla, Rolla, MO and The Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2010

Citing 4
Cited 2

Neural Network Control of Robot Manipulators and Nonlinear Systems

Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural network control of mobile robot formations using RISE feedback

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic

IEEE Transactions on Fuzzy Systems
Control of a nonholonomic mobile robot using neural networks

IEEE Transactions on Neural Networks

Robust Formation Control of Multiple Wheeled Mobile Robots

Journal of Intelligent and Robotic Systems
Fuzzy Neural Network Control for Robot Manipulator Directly Driven by Switched Reluctance Motor

International Journal of Cognitive Informatics and Natural Intelligence

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Abstract

In this paper, a combined kinematic/torque output feedback control law is developed for leader-follower-based formation control using backstepping to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers. A neural network (NN) is introduced to approximate the dynamics of the follower and its leader using online weight tuning. Furthermore, a novel NN observer is designed to estimate the linear and angular velocities of both the follower robot and its leader. It is shown, by using the Lyapunov theory, that the errors for the entire formation are uniformly ultimately bounded while relaxing the separation principle. In addition, the stability of the formation in the presence of obstacles, is examined using Lyapunovmethods, and by treating other robots in the formation as obstacles, collisions within the formation are prevented. Numerical results are provided to verify the theoretical conjectures.