Iterative Learning Control Of A Class Of Nonlinear Time-delay Systems

As the Phenomenon existed universally in the real controlled objects, time-delay is generated by some actions from transmission, measure and so on. And often results in the instability and poor performance. So it is meaningful and valuable to study the control problem for time-delay systems.In industrial process control, most complex industrial process has some repeatable properties, which enables controller designed and improved online by iterative learning, accumulating knowledge from controlled plant using a learning mechanism. In other words, on-line learning, on-line control and improvement of control system are integrated in an algorithm and realized by the repetition of industrial processes. Iterative learning control has strong advantage in solving the uncertainty problem which is caused by nonlinearity and external disturbance of the plant. It improves the system performance gradually by completing the system experience in control process. As a result, it is feasible to solve the control problem for time-delay systems with iterative learning control theory.An leading PD learning algorithm which use the leading output error of the system is developed for a class of nonlinear system with time-delay, this algorithm considers the following three conditions: the iterative initial condition as same as the desired initial condition, the iterative initial condition is fixed and the iterative initial condition is random. The convergence of this PD iterative learning algorithm was discussed by this three condition, The sufficient conditions which guarantee the convergence of the closed-loop system are theoretically given, the simulation indicate that this PD iterative learning algorithm is not only suitable for system with initial iterative error but also has the rapid convergence speed, so it is verified that this algorithm is effective.