Ing. Jan Belák

This paper introduces a modified altitude hold system, designed for VTOL aircraft. The method differs from the conventional approach by blending pilot and controller commands, significantly reducing pilot workload. Authority blending ability is crucial during emergency and severe weather situations, where the feedback controller's performance can prove insufficient. The developed control law was successfully verified with extensive pilot-in-the-loop simulations, utilizing the Tustin model of manual control. The resulting algorithm demonstrated smooth command blending throughout the flight envelope, enhancing safety and performance of VTOL aircraft operations in urban environment.

The current era of electrification of the aerospace industry brings many challenges, but also brings forward radically new aircraft designs. The new eVTOL and eSTOL concepts were enabled by the distributed electric propulsion. Even though eVTOL and eSTOL projects are gaining a lot of attention, another concept is also notable. The so-called High-Lift propulsion is based on the increase of airflow over the wing, thus reducing landing speed. Most notable example is NASA’s X-57 Maxwell. However, this concept can be used to control the aircraft as well. This paper introduces new approach of aircraft control using distributed High-Lift propulsion concept. The controller uses differential thrust to completely control the aircraft states and therefore eliminates the need for traditional control surfaces.

This paper introduces a unified approach to attitude control of tilt-rotor aircraft. The method utilizes moments-based actuation, based on real-time local linearization and LTI feedback systems. The main advantage of our approach is that it relies on fixed gain control laws throughout the entire flight envelope, including the transition from hover to cruise. This is achieved through sophisticated control allocation and model-matching algorithms. The method is designed with simple reconfiguration in case of an actuator failure, minimal computing power and future certification in mind. As a result, the developed algorithms were included in the development of the fly-by-wire system by a collaboration company.

The era of highly automated and namely renaissance of electric vehicles brings new vehicle interior configuration and concept of operations. The fully independent steering for each wheel vehicle concepts are reality. This paper presents a lateral control algorithm providing both low and more important high velocity dynamical steering capabilities. The main contribution of the presented work is utter decoupling of vehicle lateral motion. The car side velocity and cornering maneuver could be commanded and executed independently, assuring higher stability during high speed/highway maneuvers and unmatched nimbleness at low speed/city operations. Furthermore, the wheel side slip angle based control system provides full and independent utilization of each wheel traction ellipse in a lateral sense. Therefore the active safety on wheel level in guaranteed as the tire to road limits are actively preserved for each wheel. The resulting steer-by-wire systems seamlessly augment human driver commands and provides autonomous vehicles with active stabilization functionality.

At present, acoustic detection techniques of gunshots (gunshot detection and its classification) are increasingly being used not only for military applications but also for civilian purposes. Detection, localization, and classification of a dangerous event such as gunshots employing acoustic detection is a perspective alternative to visual detection, which is commonly used. In certain situations, to detect and localize a source of a gunshot, an automatic acoustic detection system, which can classify the caliber, may be preferable. This paper presents a system for acoustic detection, which can detect, localize and classify acoustic events such as gunshots. The system has been tested in open and closed shooting ranges and tested firearms are 9 mm short gun, 6.35 mm short gun, .22 short gun, and .22 rifle gun with various subsonic and supersonic ammunition. As “false alarms,” sets of different impulse acoustic events like door slams, breaking glass, etc. have been used. Localization and classification algorithms are also introduced. To successfully classify the tested acoustic signals, Continuous Wavelet and Mel Frequency Transformation methods have been used for the signal processing, and the fully two-layer connected neural network has been implemented. The results show that the acoustic detector can be used for reliable gunshot detection, localization, and classification.

At present, acoustic detection techniques of gunshots (gunshot detection) are increasingly being used not only for military applications but also for civilian purposes. Detection, localization, and classification of gunshots employing acoustic detection is perspective alternative to visual detection, which is commonly used. In certain situations, to detect a source of a gunshot, an automatic acoustic detection system may be preferable. This paper presents a system for acoustic detection, which can detect localize and classify acoustic events such as gunshots. Tested firearms are 9 mm short gun, 6.35 mm short gun, .22 short gun, and .22 rifle gun with various subsonic and supersonic ammunition. As “false alarms,” sets of different impulse acoustic events like door slams, breaking glass, etc. have been used. To successfully classify the tested acoustic signals, Continuous Wavelet and Mel Frequency Transformation methods have been used for the signal processing, and the fully two-layer connected neural network has been implemented. The results show that the acoustic detector can be used for reliable gunshot detection, localization, and classification.