<h2>AAS 97-154</h2>
<h2> EXPERIMENTS IN THE USE OF LEARNING CONTROL CONCEPTS TO  ELIMINATE ERROR IN CONSTANT VELOCITY BELT DRIVES                                        </h2>
<h4> Y. Hsin and R. W. Longman, Columbia University; E. J. Solcz and J. de Jong, Xerox Ccorporation                                                                           </h4>
<h2> Abstract </h2>
 Learning and repetitive control use previous experience performing specific  commands to improve the performance in future repetitions of the commands.  In  learning control the system returns to the same initial condition before each  repetition, and the computations can be made in a batch mode between repetitions.   In repetitive control the command or disturbance is periodic, but the system keeps  running without resetting the initial conditions.  Here we develop conditions for  convergence when the repetitive control problem is addressed in a batch mode by  applying learning action, waiting for steady state behavior, learning from this  data, adjusting the command, and repeating.