RBF network architecture for motion planning and attitude stabilization of nonholonomic spacecraft/manipulator systems

In this paper, we present a technique for planning and stabilization of motion in a class of multivariable nonlinear (nonholonomic) systems, and apply this technique to the free-flying manipulators. The controller architecture designed in the paper is based on the radial basis function (RBF) network approximation of an optimal control program for any desired motion. An additional control level for sampled feedback compensation of the approximation errors is also proposed. The presented RBF-based control technique overcomes certain problems associated with other control approaches recently proposed for nonholonomic systems. An example and numerical simulations are provided for illustration