The adaptive control system of quadrocopter motion

In this paper we present a system for automatic control of a quadrocopter based on the adaptive control system. The task is to ensure the motion of the quadrocopter along the given route and to control the stabilization of the quadrocopter in the air in a horizontal or in a given angular position by sending control signals to the engines. The nonlinear model of a quadrocopter is expressed in the form of a linear non-stationary system

Automatic Taxi Directional Control System of Carrier-based Aircraft

This paper solves the problem of automatic taxiing direction control of carrier-based aircraft. On modern aircraft carriers, taxiing aircraft either propel themselves using their own engines or are towed by specialised tugs, which requires dedicated personnel and assets. The automatization of this process would simultaneously increase aircraft flow and decrease the number of personnel and assets required. The key challenge in the automatization of this type of process is the development of an automatic control system capable of performing the requisite tasks, which our researchers managed to do. First, the specific conditions of taxiing on-board carriers were analysed and modelled. The model of a fixed-wing aircraft best suited to this purpose was identified and the proper method of automatic control – ADRC – chosen. The algorithm used in the method to facilitate effective direction control of a taxiing aircraft was formulated and extensively tested. The results of automatic taxiing simulation for F/A-18 aircraft have been presented. The conclusion is that the ADRC type control algorithm can ensure effective automatic control of taxiing aircraft

POSITION CONTROL OF VTOL SYSTEM USING ANFIS VIA HARDWARE IN THE LOOP

Electric motors have been widely applied in various equipment. One application is found in Unmanned Aerial Vehicles (UAVs). An electric motor speed control system that can balance the aircraft's position is one of the mandatory features that must be owned by the aircraft. The position balancer control also supports the Vertical Take-Off Landing (VTOL) system. This study's VTOL position control system uses Hardware-in-the-loop (HIL) method with MATLAB Simulink and Arduino. ANFIS (Adaptive Neuro-Fuzzy Inferences System) is used as a position control algorithm. The controller performance is compared with conventional PID and FLC (Fuzzy Logic Controller). The system is tested as an initial position variation and loading test. The experiment shows that HIL can help fast prototyping by faster changes in the controller algorithms and is easy to program. The result is varied in each experiment. In the ISE (Integral Square of Error) point of view, ANFIS is better than PID by 100 % and has a very small difference from FLC in the initial position test. ANFIS is better by 95.44% and 4.56% compared with PID and FLC in the loading test, respectively

Intelligent control of miniature holonomic vertical take-off and landing robot

This paper discusses the development of a fuzzy based controller for miniaturized unmanned aerial vehicle (UAV).This controller is designed to control the center-of-gravity (CoG) in a new configuration of coaxial miniaturized flying robot (MFR). The idea is to shift the CoG by controlling two pendulums located in perpendicular directions; each pendulum ends with a small mass. A key feature of this work is that the control algorithm represents the original nonlinear function that describes the dynamics of the proposed system. The controller model incorporates two cascaded subsystems: PD and PI fuzzy logic controllers. These two controllers regulate the attitude and the position of the flying robot, respectively. A model of the proposed controllers has been developed and evaluated in terms of stability and maneuverability. The results show that the presented control system can be used efficiently for the MFR applications

A synthesis of logic and bio-inspired techniques in the design of dependable systems

Much of the development of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that effectively combines these two techniques, schematically founded on the two pillars of formal logic and biology, from the early stages of, and throughout, the design lifecycle. Such a design paradigm would apply these techniques synergistically and systematically to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems, presented in the scope of the HiP-HOPS tool and technique, that brings these technologies together to realise their combined potential benefits. The paper begins by identifying current challenges in model-based safety assessment and then overviews the use of meta-heuristics at various stages of the design lifecycle covering topics that span from allocation of dependability requirements, through dependability analysis, to multi-objective optimisation of system architectures and maintenance schedules

Low-cost navigation and guidance systems for unmanned aerial vehicles - part 1: Vision-based and integrated sensors

In this paper we present a new low-cost navigation system designed for small size Unmanned Aerial Vehicles (UAVs) based on Vision-Based Navigation (VBN) and other avionics sensors. The main objective of our research was to design a compact, light and relatively inexpensive system capable of providing the Required Navigation Performance (RNP) in all phases of flight of a small UAV, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN were compared and the Appearance-Based Approach (ABA) was selected for implementation. Feature extraction and optical flow techniques were employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we addressed the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, as well as the aiding from Aircraft Dynamics Models (ADMs)