A New AILC for a Class of Nonlinearly Parameterized Systems with Unknown Delays and Input Dead-Zone

Abstract EN

This paper presents an adaptive iterative learning control (AILC) scheme for a class of nonlinear systems with unknown time-varying delays and unknown input dead-zone.

A novel nonlinear form of deadzone nonlinearity is presented.

The assumption of identical initial condition for ILC is removed by introducing boundary layer functions.

The uncertainties with time-varying delays are compensated for with assistance of appropriate Lyapunov-Krasovskii functional and Young’s inequality.

The hyperbolic tangent function is employed to avoid the possible singularity problem.

According to a property of hyperbolic tangent function, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function (CEF) in two cases, while maintaining all the closed-loop signals bounded.

Finally, a simulation example is presented to verify the effectiveness of the proposed approach.