Lateral automatic landing guidance law based on risk-state model predictive control

A lateral automatic carrier landing system (ACLS) control law is proposed for carrier-based aircraft, which could suppress the landing risk and increase the control precision. The nonlinear lateral landing equation is transformed into a polytopic model with a serial of state bounds. The landing risk including approach and arresting risks is proposed, and a Kalman filter is used to integrate both risks to construct the landing risk model. The concept of virtual state deviations is adopted by the output augment, which is estimated by an observer. The risk-state model predictive control (MPC) is established on the basis of the landing risk gradient composed of virtual states and time-varying weights. A compared simulation is tested on a semi-physical platform, which verifies excellent performance of the proposed method.