Attitude regulation for unmanned quadrotors using adaptive fuzzy gain-scheduling sliding mode control

This paper addresses the problem of attitude regulation for unmanned quadrotors with parametric uncertainties and external disturbances. A novel adaptive fuzzy gain-scheduling sliding mode control (AFGS-SMC) approach is proposed for attitude regulation of unmanned quadrotors. First, the kinematics model and dynamics model of attitude motion are derived, and the problem of attitude regulation is formulated. Second, a sliding mode controller is designed to regulate the attitude motion for its invariant properties to parametric uncertainties and external disturbances. The global stability and error convergence of the closed-loop system are proven by using the Lyapunov stability theorem. In order to reduce the chattering induced by continual switching control of SMC, the fuzzy logic system (FLS) is employed to design the AFGS-SMC, in which the control gains related to sign function are scheduled adaptively according to fuzzy rules, with sliding surface and its differential as FLS inputs and control gains as FLS outputs. Finally, the effectiveness and robustness of the proposed control approach are demonstrated via simulation results.