A NEURO-CONTROLLER FOR SYNCHRONIZATION OF 2 MOTION AXES

The coordinated and synchronized control of the motion of multiple axe s is a challenging problem in motion control fields. In most multiaxis applications, controllers are usually designed for each of the motion axes, which results in a collection of decoupled single input and sin gle output systems. For coordinated motion, however, decoupling someti mes causes damage to the overall performance objective. Therefore, a b etter way to control multiaxis systems is to introduce intelligent con trol actions in the controller so that the coordination objective of t he desired motion is maintained. A method for achieving the synchroniz ation of two motion axes using a neural network is described. We intro duce a new cost function for better synchronization performance. Also, we derive a learning law to adjust the weights of the neural network, based on the gradient algorithm. The derived learning law guarantees good synchronization performance of two motion axes. Simulation and ex perimental results demonstrate the usefulness of the proposed scheme t o synchronize the motion of multiple axes. (C) 1998 John Wiley & Sons, Inc.