Robust Adaptive Backstepping Control of Quadrotors With Unknown Input Gains

Robust adaptive tracking control design for quadrotors with unknown parameters, including the thrust and the drag factors, is presented. Firstly, the adaptive linearizing control approach is employed for conquering the issues of unknown input gains in both the outer- and inner-loop design steps. Secondly, based on the barrier Lyapunov function (BLF) method, a robust virtual controller is constructed in the intermediate design step for counteracting the coupling nonlinearity and speeding up the convergence at the same time. Thirdly, the dynamic surface control (DSC) technique is applied for alleviating the measurement of acceleration signals and explosion of complexity problem simultaneously. Last, the serial-parallel identification model (SPIM) based composite update algorithms are incorporated for further improving the tracking performance. In particular, the prediction errors are ensured to converge to the vicinity of zero without relying on the parameter convergence. Simulation studies demonstrating its validity are carried out in the final.