中文摘要：

The nonlinear aircraft model with heavy cargo moving inside is derived by using the separation body method, which can describe the influence of the moving cargo on the aircraft attitude and altitude accurately. Furthermore, the nonlinear system is decoupled and linearized through the input–output feedback linearization method. On this basis, an iterative quasi-sliding mode(SM)flight controller for speed and pitch angle control is proposed. At the first-level SM, a global dynamic switching function is introduced thus eliminating the reaching phase of the sliding motion.At the second-level SM, a nonlinear function with the property of ‘‘smaller errors correspond to bigger gains and bigger errors correspond to saturated gains’ ’ is designed to form an integral sliding manifold, and the overcompensation of the integral term to big errors is weakened. Lyapunovbased analysis shows that the controller with strong robustness can reject both constant and time-varying model uncertainties. The performance of the proposed control strategy is verified in a maximum load airdrop mission.

英文摘要：

The nonlinear aircraft model with heavy cargo moving inside is derived by using the sep- aration body method, which can describe the influence of the moving cargo on the aircraft attitude and altitude accurately. Furthermore, the nonlinear system is decoupled and linearized through the input~utput feedback linearization method. On this basis, an iterative quasi-sliding mode （SM） flight controller for speed and pitch angle control is proposed. At the first-level SM, a global dynamic switching function is introduced thus eliminating the reaching phase of the sliding motion. At the second-level SM, a nonlinear function with the property of ＂smaUer errors correspond to bigger gains and bigger errors correspond to saturated gains＂ is designed to form an integral sliding manifold, and the overcompensation of the integral term to big errors is weakened. Lyapunov- based analysis shows that the controller with strong robustness can reject both constant and time-varying model uncertainties. The performance of the proposed control strategy is verified in a maximum load airdrop mission.