On the Learning Control Scheme for Linear Systems
Takuya SOGO, Norihiko ADACHI
In this paper the iterative learning control scheme is considered from the standpoint of minimizing the special case of quadratic cost criterion for linear systems.
First, an iterative learning control scheme based on the gradient method is proposed. It can be applied to any plant if the full information of the adjoint system is available.
Second, an iterative learning control scheme for unknown plants is proposed. Since the convergent condition of the scheme is equivalent to the input-output condition of the second block of cascade-connected adjoint systems, the applicable range of the scheme is determined by the amount of the available information of system models.
Consequently, it is proved that the problem of designing iterative learning control schemes is equivalent to the problem of decomposing adjoint systems.