Autonomous Landing of an UAV Using H∞ Based Model Predictive Control

Possibly the most critical phase of an Unmanned Air Vehicle (UAV) flight is landing. To reduce risk due to pilot error, autonomous landing systems can be used. Environmental disturbances such as wind shear jeopardize safe landing, therefore a well-adjusted and robust control system required maintain performance requirements during The paper proposes loop-shaping-based Model Predictive Control (MPC) approach for UAV landings. Instead conventional MPC plant model augmentation, input output weights are designed in frequency domain meet transient steady-state requirements. Then, H∞ loop shaping design procedure used synthesize state-feedback controller shaped plant. This linear law then solve inverse optimization problem cost function matrices MPC. inherits small-signal characteristics when constraints inactive (i.e., perturbation around equilibrium points that keep within saturation limits). synthesis results observer plus state feedback structure. estimator initializes at each time step. successfully evaluated non-linear simulation environment under moderate severe downburst. It rejects unmeasured disturbances, has good performance, provides excellent stability margin, enforces constraints.