Mathematical model of an unmanned aerial vehicle with four propulsors (quadcopter) is indispensable in quadcopter movement simulation and later modelling of the control algorithm. Mathematical model is, at the same time, the first step in comprehending the mathematical principles and physical laws which are applied to the quadcopter system. The objective is to define the mathematical model which will describe the quadcopter behavior with satisfactory accuracy and which can be, with certain modifications, applicable for the similar configurations of multirotor aerial vehicles. At the beginning of mathematical model derivation, coordinate systems are defined and explained. By using those coordinate systems, relations between parameters defined in the earth coordinate system and in the body coordinate system are defined. Further, the quadcopter kinematic is described which enables setting those relations. Also, quadcopter dynamics is used to introduce forces and torques to the model through usage of Newton-Euler method. Final derived equation is Newton's second law in the matrix notation. For the sake of model simplification, hybrid coordinate system is defined, and quadcopter dynamic equations derived with the respect to it. Those equations are implemented in the simulation. Results of behavior of quadcopter mathematical model are graphically shown for four cases. For each of the cases the propellers revolutions per minute (RPM) are set in a way that results in the occurrence of the controllable variables which causes one of four basic quadcopter movements in space.

The development of multirotor unmanned aerial vehicles (UAVs) has enabled a vast number of applications. Since further market growth is expected in the future it is important that modern engineers be familiar with these types of mechatronic systems. In this paper, a comprehensive mathematical description of a multirotor UAV, with various configuration parameters, is given. A modular design approach for the development of an educational multirotor platform is proposed. Through the stages of computer-aided design and rapid prototyping an experimental modular multirotor (EMMR) platform is presented. Open-source control system and a novel EMMR enable students to create and test control algorithms for various multirotor configurations. The presented EMMR platform is suitable for students to expand their educational objectives in aerial robotics and control theory.

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A key drawback of multirotor unmanned aerial vehicles (UAVs) with energy sources based solely on electrochemical batteries is related to the available on-board energy. Flight autonomy is typically limited to 15–30 min, with a flight duration upper limit of 90 min currently being achieved by high-performance battery-powered multirotor UAVs. Therefore, propulsion systems that utilize two or more different energy sources (hybrid power systems) may be considered as an alternative in order to increase the flight duration while retaining key performance benefits of battery energy storage use. The research presented in this work considers a multirotor UAV power unit, based on the internal combustion engine (ICE) powering an electricity generator (EG) connected to the common direct current (DC) bus in parallel with the lithium-polymer (LiPo) battery, and the respective modeling and identification of individual power unit subsystem, along with the dedicated control system design. Experimental verification of the proposed hybrid power unit control system has been carried out on the custom-build power unit prototype. The results show that the proposed control system combines the two power sources in a straightforward and effective way, with subsequent analysis showing that a two-fold energy density increase can be achieved with a hybrid energy source, consequently making it possible to achieve higher flight autonomy of the prospective multirotor (hover load around 1000–1400 W) equipped with such a hybrid system.

In this paper, a frequency-shifting-based (FSB) algebraic approach to stable on-line parameter identification and state estimation is proposed. The proposed simultaneous parameter identification and state estimation algebraic approach are applied to multirotor adaptive-like tracking control assuming that only position measurement is available. The proposed algebraic approach provides very fast convergence towards true values of system parameters and states, without transients that depend on initial conditions and without peaking phenomenon which is characteristics of high-gain observers. The efficiency of the proposed algorithm is illustrated by a simulation example.