A novel approach to the control of quad-rotor helicopters using fuzzy-neural networks

Quad-rotor helicopters are agile aircraft which are lifted and propelled by four rotors. Unlike traditional helicopters, they do not require a tail-rotor to control yaw, but can use four smaller fixed-pitch rotors. However, without an intelligent control system it is very difficult for a human to successfully fly and manoeuvre such a vehicle. Thus, most of recent research has focused on small unmanned aerial vehicles, such that advanced embedded control systems could be developed to control these aircrafts. Vehicles of this nature are very useful when it comes to situations that require unmanned operations, for instance performing tasks in dangerous and/or inaccessible environments that could put human lives at risk. This research demonstrates a consistent way of developing a robust adaptive controller for quad-rotor helicopters, using fuzzy-neural networks; creating an intelligent system that is able to monitor and control the non-linear multi-variable flying states of the quad-rotor, enabling it to adapt to the changing environmental situations and learn from past missions. Firstly, an analytical dynamic model of the quad-rotor helicopter was developed and simulated using Matlab/Simulink software, where the behaviour of the quad-rotor helicopter was assessed due to voltage excitation. Secondly, a 3-D model with the same parameter values as that of the analytical dynamic model was developed using Solidworks software. Computational Fluid Dynamics (CFD) was then used to simulate and analyse the effects of the external disturbance on the control and performance of the quad-rotor helicopter. Verification and validation of the two models were carried out by comparing the simulation results with real flight experiment results. The need for more reliable and accurate simulation data led to the development of a neural network error compensation system, which was embedded in the simulation system to correct the minor discrepancies found between the simulation and experiment results. Data obtained from the simulations were then used to train a fuzzy-neural system, made up of a hierarchy of controllers to control the attitude and position of the quad-rotor helicopter. The success of the project was measured against the quad-rotor’s ability to adapt to wind speeds of different magnitudes and directions by re-arranging the speeds of the rotors to compensate for any disturbance. From the simulation results, the fuzzy-neural controller is sufficient to achieve attitude and position control of the quad-rotor helicopter in different weather conditions, paving way for future real time applications

Computational fluid dynamics model of a quad-rotor helicopter for dynamic analysis

The control and performance of a quad-rotor helicopter UAV is greatly influenced by its aerodynamics, which in turn is affected by the interactions with features in its remote environment. This paper presents details of Computational Fluid Dynamics (CFD) simulation and analysis of a quadrotor helicopter. It starts by presenting how SolidWorks software is used to develop a 3-D Computer Aided Design (CAD) model of the quad-rotor helicopter, then describes how CFD is used as a computer based mathematical modelling tool to simulate and analyze the effects of wind flow patterns on the performance and control of the quadrotor helicopter. For the purpose of developing a robust adaptive controller for the quad-rotor helicopter to withstand any environmental constraints, which is not within the scope of this paper; this work accurately models the quad-rotor static and dynamic characteristics from a limited number of time-accurate CFD simulations

Modelling and simulation of a quad-rotor helicopter

Small size quad-rotor helicopters are often used due to the simplicity of their construction and maintenance, their ability to hover and also to take-off and land vertically. The first step in control development is an adequate dynamic system modelling, which should involve a faithful mathematical representation of the mechanical system. This paper presents a detailed dynamic analytical model of the quad-rotor helicopter using the linear Taylor series approximation method. The developed analytical model was simulated in the MatLab/Simulink environment and the dynamic behaviour of the quad-rotor assessed due to voltage changes. The model is further calibrated and linearized for use on any quad-rotor helicopter

Design of Self-tuning PID Controller Parameters Using Fuzzy Logic Controller for Quad-rotor Helicopter

This paper presents the design of a Fuzzy PID controller (FPID) based on fuzzy logic with a PID structure with many valued logic and reasoning. The self-turning Fuzzy PID control take in an error and the rate of change of error of the altitude and attitude of the quadrotor as the input to the fuzzy controller and use the fuzzy rules to adjust the PID parameter automatically. Simulations have been conducted to observe the differences in controlling the quadrotor in flight using the new FPID controller instead of using PID controller. The effectiveness of the developed FPID is verified using the dSPACE platform whereby the Simulink model of the controller is converted to a real time system to generate the control signals for the control of quad rotor helicopter