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

• Published in: Drones (Basel) 2022-12, Vol.6 (12), p.416
• Main Authors: Latif, Zohaib, Shahzad, Amir, Bhatti, Aamer Iqbal, Whidborne, James Ferris, Samar, Raza
• Format: Article
• Language: English
• Subjects: Altitude; autonomous landing; Control algorithms; Control systems; Control theory; Controllers; Cost function; Design; Design optimization; Disturbances; Feedback control; Fuzzy logic; H-infinity control; Human error; H∞ synthesis; Landing aids; MPC; Optimization; Perturbation; Pilot error; Predictive control; Robust control; Sensors; State estimation; State feedback; State observers; Transient performance; UAV; Unmanned aerial vehicles; Wind shear
• ISSN: 2504-446X; 2504-446X
• DOI: 10.3390/drones6120416

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.