Automatic landing of fixed-wing aircraft with constrained algebraic model predictive control

This article proposes an algebraic model predictive control (MPC) method for automatic landing. While defining the constraint functions in the optimization problem, the tangent hyperbolic function is preferred. Therefore, the optimization problem turns into an unconstrained, continuous, and differentiable form. An analytical two-step method is also proposed to solve the rest of the problem. In the first step, it is assumed that only input constraints are active and states are unconstrained. The optimal solution for this case is calculated directly with the optimality condition. The calculated control signal is revised in the second step according to system dynamics and state constraints. Simulation results of the auto-landing system show that the MPC computation speed is significantly increased by the new algebraic MPC (AMPC) without compromising the control performance, which makes the method realistic for using MPC in systems with high-speed changing dynamics.