Contents 1. Introduction
There is a growing interest in the field of UAVs due to its numerous applications both commercial and noncommercial. UAVs use various configurations such as bicopoter, tricopter, quadcopter, hexacopter etc. depending on the number of rotors used. A quadcopter is a special case where four rotors are used. By varying the speed and direction of these rotors the quadcopter can be efficiently maneuvered. High degree of maneuverability of quadcopters can be achieved with enhanced payload [1]. In a quadcopter the six degrees of freedom are controlled by only four inputs i.e., through the four rotors. Hence this type of system is known as underactuated system. The control design of such system is a very challenging task [2]. There has been a lot of work which are revolving around this research area. Some of the relevant work is given here. In quadcopter system the linear PID controller is widely used for their simplicity. In [3] PID control has been used to control both attitude and altitude of a quadcopter. In [4] the quadcopter was controlled by using the trajectory tracking control design. Through the literatures, it is generally established that the PID controller has been precisely applied to the quadrotor though with some limitations. The tuning of PID controller around an equilibrium hovering point gives a major limitation. In PID controller when the unmodelled disturbances are large, it decreases the range of operation for a quadcopter. In LQR control where optimal control algorithm minimizes a suitable cost function, is also widely used in quadcopter control. A simple path following LQR controller was given by cowling et al. in [5]. Sliding mode controller are also used for precise and accurate control of the quadcopter. The sliding mode controller was applied to stabilize cascaded under-actuated systems in [6]–[8]. But this controller has some limitation as this produces chattering in the system due to the faster switching. Now a days some of the hybrid controllers are used such as fuzzy PID controller, ANN (artificial neural network) based PID controllers etc. But these types of controllers make the system complex. Hence in most of the industrial applications the PID controller which is very simple is being used even though it has many limitations as stated above. Hence the need of the hour is to develop a linear controller which is very simple like PID controller but yet again very precise and accurate like some of the non-linear controller. The multielement viscoelastic controllers have been very successful in rotor dynamics [9] [10]. But these controllers are not tested for underactuated systems like Quadcopters. Hence here a controller which imitates the behavior of four element viscoelastic material is proposed to control the quadcopter. Hence this controller is called FE controller. The controller is than compared with the classical PID controller in the presence of unmodelled disturbances and some given time delay. Both the models are simulated in the Simulink interface.
