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

Abstract

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

Autonomous Landing of Quadrotor Unmanned Aerial Vehicles Based on Multi-Level Marker and Linear Active Disturbance Reject Control

“…MPC was used for autonomous landing, different from conventional methods, and a synthesized state feedback was formed by the H∞. The method had good performance on disturbance rejection and transient characteristics [ 21 ]. In view of the problem of quadrotor UAV flight control being disturbed by wind, a dynamic model based on the wind tunnel test was established, and the response characteristics of discrete and continuous wind disturbances were obtained [ 22 ].…”

Frequency-dependent control for wind disturbance rejection of a fully actuated UAV

“…Vectors expressed by W, B, and M i are expressed in the world, body, and ith-motor frame, respectively. (1,4,5,8) are tilted about the body x-axis, while the left and right rotors (2,3,6,7) are tilted around the body y-axis. The rotors of the UAV are equally distributed around the center of mass.…”

“…and C M,i (α i , λ i ) are dimensionless aerodynamic coefficients defined in ref. [6]. Due to the offset between the rotors and the center of mass of the UAV, the apparent wind velocity at each rotor is affected by the rotational speed of the UAV and is given by…”

“…Many studies have focused on active disturbance rejection with automatic control in multirotor UAVs [3,4]. H ∞ control is a well-known method for its high disturbance rejection and stability robustness, which has been widely used to address different UAV problems [5][6][7]. The combination of model predictive control and H ∞ was designed for the wind disturbance rejection of quadrotors in simulation [8,9].…”