Iterative Learning Based Nonlinear Sliding Mode Control for the Single‐Link Flexible Manipulator

ABSTRACT Due to the presence of flexible components, strong coupling dynamics, underactuation, and non‐minimum‐phase characteristics, achieving simultaneous high‐precision motion tracking and rapid vibration suppression remains a longstanding challenge for flexible manipulators. In this paper, we propose an iterative learning–based nonlinear sliding mode control (IL‐NSMC) scheme for a single‐link flexible manipulator (SLFM). The proposed scheme comprises two synergistic components: (i) a nonlinear sliding mode controller (NSMC) whose sliding surface embeds the rate of flexible vibration energy, in contrast to conventional SMC, whose sliding surface depends solely on the rigid‐joint error and (ii) an iterative learning control (ILC) module that exploits trajectory repetition to compensate for the lumped deviation induced by model uncertainties and external disturbances, requiring no prior knowledge of their bounds and thereby permitting a substantially lower robust gain, which in turn alleviates the chattering that conventional SMC introduces into flexible structures. Convergence in both the time and iteration domains is established via a composite Lyapunov analysis. Comparative simulation studies against conventional sliding mode control (SMC) and multivariable feedback control (MFC) validate the superior effectiveness, feasibility, and practicality of the proposed approach.