Michal Lower

Fuzzy flight control system for helicopter intelligence in hover

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 experts analysis (pilots knowledge). The helicopters 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.

Air Traffic Incidents Analysis with the Use of Fuzzy Sets

In safety, reliability as well as risk analysis and management, information often is uncertain and imprecise. The approach to air incident analysis under uncertain and imprecise information presented in our paper is inspired by the possibility theory. Notably, in such analyses these are both: static and dynamic components that have to be included. As part of this work, static analysis of a serious incident has been performed. In order to do this, probability scale which is based on fuzzy set theory has been given. The scenarios of transformation of incident into accident have been found and their fuzzy probabilities have been calculated. Finally, it has been shown that elimination of one of premises for transformation of the incident into accident significantly reduces the possibility of this transformation.

Analysis of Air Traffic Incidents using event trees with fuzzy probabilities

This paper presents a methodology for analysing Air Traffic Incidents based on an estimate of the probability of an Air Traffic Incident developing into an Air Traffic Accident (Air Traffic Incidents are officially defined as events which are dangerous but without a catastrophic impact). A new approach is presented as previous research in this area has focused more on defining accident occurrence probabilities. Access to detailed information on Air Traffic Incidents is limited and for this reason the methodology developed was based on Fuzzy Set Theory. Analysis was carried out using Event Trees leading from a real Incident to a hypothetical Accident with the probabilities of occurrence of the various scenarios being defined by fuzzy sets. The results of this analysis enable the calculation of the fuzzy probability of the Incident being transformed into an Accident. Performing this analysis, new measuring techniques for the comparison of fuzzy sets were developed and partially verified. The Case Study presented in the paper analyses a Serious Runway Incursion Incident. This Serious Incident is analysed for influencing factors such as: pilot and flight controller skill levels, airport traffic volume, weather conditions, airport procedures and airport geometry. Applying the methods presented in this paper enables an assessment of the effectiveness of Preventive Recommendations of Accident/Incident Investigation Commissions. Additionally, probability estimations can be developed for different incident situations allowing the identification of Security System Weak Points thus enabling appropriate proactive measures to be taken for their elimination. Fuzzy probability of a serious air traffic incident developing into an accident.New measures for comparing fuzzy sets and their properties.Events importance and sensitivity analysis of the incident.Analysis of the State Commission for Aircraft Accident Investigation recommendation.

Stabilisation and steering of quadrocopters using fuzzy logic regulators

The cascaded fuzzy controller system for quadrocopter was developed on the basis of computer simulations. The mathematical model of quadrocopter and its cascaded fuzzy controller were simulated using Matlab Simulink software. The proposed controller was tested in most frequent flight circumstances: in hover, in rectilinear flight with constant speed, in climbing and in rotation. In all these situations the proposed controller was able to provide foreseeable behavior of the quadrocopter.

Selection and Setting of an Intelligent Fuzzy Regulator based on Nonlinear Model Simulations of a Helicopter in Hover

Most research on fuzzy regulators has focused on the integrating rules in intelligent control systems. This paper evaluates a fuzzy helicopter regulator for a single-rotor PZL Kania helicopter. Unlike other models which only match stable flight ability, the model presented in this paper attempts to match the links between disturbances and hover conditions. Two simulations were performed to validate the model. In the first simulation, a helicopter was evaluated in a fixed hover position. In the second simulation, model robustness was validated by introducing wind gust. Results, both with the initial and with the modified model demonstrated the viability of the proposed regulator.

Helicopter Intelligence in Hover Quality Improvement of the Fuzzy Regulator

The modified model of the fuzzy control system was developed on the basis of computer simulation experiments. The helicopters 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 in hovering with and without coupling between helicopter response on steering moves. The fuzzy flight control system proposed was able to provide a stable behavior of the helicopter under all simulated circumstances

Building the fuzzy control system based on the pilot knowledge

The main problem addressed in this paper is simplification of transforming the knowledge from natural language description to fuzzy rules control system. The proposed fuzzy system build on the observation of human pilot reaction and on few very simple rules is very promising. Our fuzzy control system allow to control the helicopter in the hover yet can be generalize to other aspect of helicopter flight.

On quadrotor navigation using fuzzy logic regulators

In this paper the cascaded fuzzy controller system for quadrotor steering and stabilizing was deliberated. The mathematical model of quadrotor and its cascaded fuzzy controller were simulated using Matlab Simulink software. The fuzzy system was divided into three subsystems for controlling position and speed of the quadrotor and for steering rotation speed of propellers. In the article the square trajectory of quadrotor flight was presented as a system test.

Evaluation of the Location of the P&R Facilities Using Fuzzy Logic Rules

The trend of limiting vehicular traffic to the benefit of public transport is developed in contemporary urban planning. One of the tasks is determining location of the collective parking places in the P&R system. Criteria for assessing the quality of the selected location are formulated generally and descriptively. However, the factors to be assessed are often ambiguous and fuzzy, difficult to be precisely determined but possible for the evaluation by an expert. Due to the large number of parameters of criteria the practice has shown that the choice of the location of these sites in a way that is intuitive without a detailed analysis of all the circumstances, often gives negative results. Then the existing facilities are not used as expected. The authors have used fuzzy inference to the evaluation of the location of the P&Rs based on fuzzy input parameters. The obtained results of the analysis allows to determine the degree of attractiveness of the selected place on the basis of a broad set of the expert input data. The proposed evaluation method has been tested on three existing facilities for which the effect is already known.

Quadrotor Navigation Using the PID and Neural Network Controller

In this paper the neural network controller for quadrotor steering and stabilizing under the task of flight on path has been deliberated. The control system was divided into four subsystems. Each of them is responsible for setting the control values for controlling position and speed of the quadrotor and for steering rotation speed of propellers. The neural network was taught by control system with standard PID controller. This approach is used for checking how neural networks cope with stabilisation of the quadrotor under flight task. Simulation results of the neural controller and PID controller working were compared to each other. The mathematical model of quadrotor and its neural controller were simulated using Matlab Simulink software. In the paper the simulation results of the quadrotor’s flight on path of are presented.