This paper presents a repetitive learning control scheme to handle systems subject to both time-delay and dead-zone nonlinearities and the state-dependent input gain simultaneously. The adaptive bounding techniques are utilized to deal with the nonparametric uncertainties originated from the time-delay and the state-dependent input gain, in which the indirect learning manner is employed to avoid the appearance of the sign function, alleviating the requirement for the system information. The only prior knowledge of the proposed scheme is the lower bound of the input gain and the dead-zone slope. The desired control signal is recognized as the parametric uncertainties with a constant regressor. The derivation of the convergence analysis is provided in detail, and the boundedness of variables in the closed-loop system is guaranteed. The numerical simulation is conducted to testify the effectiveness of the presented control approach.
Li et al. (Fri,) studied this question.