A Design of Learning Control System for Linear Multivariable Systems

Iterative Learning Control for Multiple Point-to-Point Tracking Application

“…The system can be represented using the continuous time plant transfer function (74) which has been identified in previous work [19]. The adjoint ILC algorithm is selected as a well known member of the class considered, and is given in discrete form by (75) where is the adjoint of the plant model used (see [21] for theoretical background). An attractive feature of the method is that, with a sufficiently small positive scalar multiplier, , it is guaranteed to satisfy the condition for monotonic convergence over all frequencies, and hence ensure a satisfactory transient response [22].…”

“…The norm error ratio is (21) and the proposed objective-driven ILC has introduced the multiplier on the th frequency component. This multiplier relaxes the monotonic convergence criterion given by (10).…”

Norm-Optimal Iterative Learning Control with Application to Problems in Accelerator-Based Free Electron Lasers and Rehabilitation Robotics

“…There are many iterative procedures to solve the optimization problem (3) but there is a clear advantage in the use of descent algorithms of a suitable type as considered for learning systems by, for example, [20]. The gradientbased ILC algorithm class generates the control input to be used on trial k + 1 as…”

Iterative Learning Control — Monotonicity and Optimization

“…ILC algorithms are commonly applied in situations that are typified by Although a number of results have been obtained in each case (see, e.g., Chen and Wen, 1999;Harte and Owens, 2005;Furuta and Yamakita, 1987), it is fair to say that theoretical knowledge and CAD tools relevant to the understanding of these problems are currently very limited. Much more work is needed in this area.…”