Modeling and adaptive hybrid fuzzy control of a nonlinear rotor system

Abstract

The paper deals with the hierarchical modeling, simulation and model-based investigation of a nonlinear 1 DOF helicopter model, which is the most important building block of complex multi-rotor systems. The motivation behind the work is the increasing number of multi-rotor drones with various applications in diverse areas like smart cities and smart infrastructures, such as intelligent surveillance, autonomous (or semi-autonomous) flight, automatic object detection and recognition, carrying various payloads (sensors, packages) etc. In order to make these flying robots intelligent, a sophisticated control strategy is required, which is partly based on sensory information provided by the on-board sensors (gyroscope, accelerometer)-recently supported by visual data provided by on-board camera(s)-concerning the low-level feedback control loops. Most of the modern drones are built on an embedded computer, and the first layer of control is usually implemented in the firmware, thus the low level control commands are given per se. For the accomplishment of complex tasks (specific "behavior" of the drone) high level control strategies have to be implemented. In order to make these control loops efficient and robust, model based analysis of the controlled system had been carried out along with the real-life tests of the various control strategies. Since both the structure and the parameter set of the model system can be easily changed, model based study is a very efficient way of experimenting with novel control approaches.