In adaptive model-based control systems, determining the appropriate controller gain is a complex and time-consuming task due to noise and external disturbances. Changes in the controller parameters were assumed to be dependent on the quadcopter mass, which was the process variable. A nonlinear model of the plant was used to identify the mass, employing the weighted recursive least squares (WRLS) method for online identification. The identification and control processes involved filtration using differential filters, which provided appropriate derivatives of signals. Proportional integral derivative (PID) controller tuning was performed using the Gauss–Newton optimisa-tion procedure on the plant. Differential filters played a crucial role in all the developed control systems by significantly reducing measure-ment noise. The results showed that the performance of classical PID controllers can be improved by using differential filters and gain scheduling. The control and identification algorithms were implemented in an National Instruments (NI) myRIO-1900 controller. The nonlinear model of the plant was built based on Newton’s equations.
At the turn of the 20th and 21st centuries, development of microelectronics and microwave techniques allowed for minimization of electronic devices and systems, and the use of microwave frequency bands for modern radio communication systems. On the other hand, the global navigation satellite system (GNSS) have contributed to the popularization of radio navigation in civilian applications. These factors had a direct impact on the development and dissemination of unmanned aerial vehicles (UAVs). In the initial period, the UAVs were used mainly for the army needs. This results also from the legal aspects of the UAV use in the airspace. Currently, commercial UAVs for civilian applications, such as image recognition, monitoring, transport, etc., are presented increasingly. Generally, the GNSS system accuracy for the UAV positioning during a flight is enough. However, the GNSS use for automatic takeoff and landing may be insufficient. The extensive, ground-based navigation support systems used at airports by manned aircraft testify to these. In the UAV case, such systems are not used due to their complexity and price. For this reason, the novel dedicated take-off and landing systems are developed. The proposal of the autonomous landing system, which is based on the Doppler effect, was presented in 2017. In this case, the square-based beacon configuration was analyzed. This paper shows the influence of various beacon configurations in the Doppler-based landing system on the positioning error during the UAV landing approach.
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