# Control and Position Tracking for UAVs
## 2 An Overview of the Published Articles  
[PERSON]'s article (contribution 1) discusses the optimal control of a tricopter UAV in programmed flights. In the study, a new approach to PID loop tuning is presented and investigated to achieve the desired performance of the tricopter by finding the optimal coefficients of the PIDs. The proposed method is effective for performing repeatable flights through predefined paths. The basis of the method is a control quality criterion, which is based on the integral of the absolute error, and its minimization allows finding the optimal PID coefficients. The authors conclude that their method could be an alternative to methods based on adaptive control, as they provide the same reliability and robustness of the control system. The results of the numerical simulations confirm that the tricopter control achieves the desired performance causing a minimal tracking error and a satisfactory short response time. The article by [PERSON] and others (contribution 2) presents results from experimental research on a multicopter tethered to the ferry deck during a normal cruise through the Baltic Sea. The main goal of the research is to synchronize the movement of both the UAV and the landing pad on the ferry to enable take-off, flight, and landing without stopping the ferry, which takes time in maritime conditions. To achieve this, a special landing pad navigational station was developed with two GNSS receivers and an electronic compass, which sends the navigational parameters of the landing pad over the radio link to the onboard computer of the UAV. The Kalman filter based on the navigational parameters of the UAV and the ferry can estimate the position of the landing pad even when the radio link is lost. During the experiment, several flights were performed, and any unnecessary power cord unwinding was not observed, whether from tension from tracking errors or wind gusts. In the tests, the power cord unwinder was also examined with automated tension control. The article by [PERSON] (contribution 3) describes the maintenance of offshore wind farms, using a fleet of UAVs. In the research, proactive and reactive path planning was presented and validated through numerical simulations. Here, proactive path planning means finding an optimal schedule at a pre-mission phase for the inspection and the service of wind turbines on the farm made by service teams with the support of the UAV. Reactive path planning for UAVs is performed during farm maintenance if the support teams request a spare part to be delivered, considering that the vessel's position, planned route, and weather conditions are known. The UAV fleet is used to deliver the required spare parts to each service vessel. The main goal of proactive path planning for the service vessels and the fleet of UAVs is to shorten the total service time as much as possible. The authors claim that the model of proactive and reactive path planning and scheduling is easy to generalize and expand with the vessel routing and staff and competence planning. The article by [PERSON] (contribution 4) is dedicated to the control of the longitudinal motion of a small fixed-wing UAV during the landing phase, which is robust against external disturbances and allows for avoiding the stalling effect by imposing prescribed state constraints. To design an effective controller to track the altitude and airspeed trajectories in the landing phase, a combination of the adaptive prescribed performance control and saturation of the generated state reference trajectories of the flight-path angle, the pitch angle, angle of attack, and pitch rate is considered. One of the advantages of the proposed method is that it is approximation-free, which means that any knowledge about system nonlinearities or any disturbance observer is not obligatory.