Adaptive iterative learning control for bilinear parameterized uncertain systems with unknown control direction

In this paper, a novel adaptive iterative learning control approach is proposed for first-order and higher- order bilinear parameterized uncertain systems with unknown control direction. For bilinear parameters problem, a differential-difference coupled-type updating law is imported. Moreover, Nussbaum-gain technique is used to solve the unknown control direction problem. According to the above, a new adaptive control strategy is designed to gua- rantee the tracking error converges to zero on a finite time domain. Then, by constructing a Lyapunov-Krasovskii-like composite energy function, a sufficient condition for the convergence and boundedness of closed-loop systems is given. Finally, two simulations are carried out to illustrate the validity and feasibility of the proposed algorithms.