Title :
Radial basis function network architecture for nonholonomic motion planning and control of free-flying manipulators
Author :
Gorinevsky, D. ; Kapitanovsky, A. ; Goldenberg, A.
Author_Institution :
Robotics & Autom. Lab., Toronto Univ., Ont., Canada
fDate :
6/1/1996 12:00:00 AM
Abstract :
This paper considers a problem of nonholonomic motion planning. A practical paradigm for planning and stabilization of motion in a class of multivariate nonlinear (nonholonomic) systems is presented and applied to a planar free-floating manipulator system. The controller architecture designed in the paper is based on the radial basis function approximation of an optimal control program for any desired motion. This architecture also incorporates a sampled-data feedback stabilization algorithm. The proposed control technique overcomes certain problems associated with other control approaches available for nonholonomic systems. The presented simulation results reveal a promising potential of the proposed control paradigm. This paradigm can be extended to a broader class of nonlinear control problems
Keywords :
feedback; feedforward neural nets; manipulators; mobile robots; motion control; neurocontrollers; optimal control; path planning; sampled data systems; stability; free-flying manipulators; motion stabilisation; multivariate nonlinear nonholonomic systems; nonholonomic motion planning; optimal control program; radial basis function network architecture; sampled-data feedback stabilization algorithm; Artificial neural networks; Attitude control; Control systems; Feedback control; Function approximation; Motion control; Open loop systems; Optimal control; Radial basis function networks; Robotics and automation;
Journal_Title :
Robotics and Automation, IEEE Transactions on