This paper relates to a fuzzy flight control system in spot hovering for a single-rotor helicopter PZL Kania. The model of the fuzzy control system was developed on the basis of computer simulation experiments done by the expert's analysis (pilot's knowledge). The helicopter's mathematical model and its fuzzy flight control system were simulated using Matlab software package. In a series of numerous computer simulations the operation of the fuzzy control system was investigated and the system itself was tuned up. Simulation tests have been performed for the helicopter both in fixed hovering, and in hovering with disturbances. Disturbances were related to a gust of wind or to an accidental motion of one of the rudders. Obtained results give the good promise for building the Web simulator.

In this paper, a nonlinear controller (TR) for an inverted pendulum using the trigonometric function is presented. The TR controller is a new proposal, which is represented by a simple mathematical formula. TR operation does not require complex calculations, so it can be applied even to the simplest microcontrollers. Tuning the TR controller is very simple, and the range of stable operation is very wide. Simulation tests of the TR controller showed that the controller is effective even for deviations exceeding 50${}^{\circ }$. The TR controller tests were compared to the results of a PID controller. The TR controller is designed to stabilise an inverted pendulum in the equilibrium point, a state in which the pendulum is in a upright position. Stabilisation for other deflection-angle set points was not taken into account. During the research, steps were taken to simulate phenomena characteristic of real solutions. An inertial block and a disturbance were introduced into the test system. Despite the introduced difficulties, the TR controller effectively stabilised the pendulum without the need to retune the controller settings. Consequently, the TR controller is an attractive alternative to previously applied solutions for the stabilisation of an inverted pendulum.

This article investigates the causes of occasional flight instability observed in Unmanned Aerial Vehicles (UAVs). The issue manifests as unexpected oscillations that can lead to emergency landings. The analysis focuses on delays in the Extended Kalman Filter (EKF) algorithm used to estimate the drone’s attitude, position, and velocity. These delays disrupt the flight stabilization process. The research identifies two potential causes for the delays. First cause is magnetic field distrurbances created by UAV motors and external magnetic fields (e.g., power lines) that can interfere with magnetometer readings, leading to extended EKF calculations. Second cause is EKF fusion step implementation of the PX4-ECL library combining magnetometer data with other sensor measurements, which can become computionally expensive, especially when dealing with inconsistent magnetic field readings. This can significantly increase EKF processing time. The authors propose a solution of moving the magnetic field estimation calculations to a separate, lower-priority thread. This would prevent them from blocking the main EKF loop and causing delays. The implemented monitoring techniques allow for continuous observation of the real-time operating system’s behavior. Since addressing the identified issues, no significant problems have been encountered during flights. However, ongoing monitoring is crucial due to the infrequent and unpredictable nature of the disturbances.