Iterative Learning Control for Large-Scale Systems
The ILC is constructed for the discrete-time large-scale systems consisting of several subsystems. Each subsystem is affine nonlinear and its observation equation is with noise. Subsystems are nonlinearly connected via the large state vector of the whole system. The possibility of data missing and communication delay is taken into account. It is proved that decentralized ILC designed in this chapter generates the input sequence that converges to the desired control minimizing the tracking error index in almost sure sense.
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