Browsing by Author "Shahzad, Amir"

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    Autonomous landing of an UAV using H∞ based model predictive control
    (MDPI, 2022-12-15) Latif, Zohaib; Shahzad, Amir; Bhatti, Aamer Iqbal; Whidborne, James F.; Samar, Raza
    ossibly 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.
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    Enhancing quadrotor resilience in outdoor operations with real-time wind gust measurement by using LiDAR
    (World Scientific Publishing, 2025-03-12) Latif, Zohaib; Whidborne, James F.; Bhatti, Aamer Iqbal; Shahzad, Amir; Samar, Raza
    Unmanned Aerial Vehicles (UAVs) encounter wind gusts during outdoor operations, impacting their position holding, particularly for quadrotors. This vulnerability is amplified during the autonomous docking to outdoor charging stations. The integration of real-time wind preview information for UAV gust rejection control has become more feasible with advances in remote wind sensor technologies like LiDAR. In this study, a ground-based LiDAR system is proposed to predict wind gusts at the landing site of quadrotors. The acquired wind preview data are subsequently utilized by the Model Predictive Control (MPC) to effectively mitigate disturbances. To validate the proposed methodology, a nonlinear simulation environment has been established using LiDAR data collected from comprehensive field tests. The results demonstrate a notable improvement in the system performance compared to benchmark results. This research underscores the practical utility of real-time wind preview information, facilitated by LiDAR technology, in enhancing the overall operational resilience of UAVs, especially quadrotors, during challenging environmental conditions.