A continuous asymptotic tracking control strategy for uncertain multi-input nonlinear systems

In this paper, we present a novel continuous control mechanism that compensates for uncertainty in a class of multi-input nonlinear systems. The control strategy is based on limited assumptions on the structure of the system nonlinearities. A Lyapunov-based stability argument is employed to prove semi-global asymptotic tracking. The control mechanism has the interesting feature of "learning" the unknown system dynamics. For the sake of clarity, the proposed control design is initially presented for a first-order, single-input case. Using this result as a stepping stone, the design is then extended to higher-order, multi-input systems.