Fuzzy Logic Based PID Auto Tuning Method of QNET 2.0 VTOL

Published Online February 2020 in MECS DOI: 10.5815/ijitcs.2020.01.02

A rapid increase can be seen in the study of unmanned aerial vehicles’ modeling and control. The use of UAVs is growing rapidly across many application domains including search rescue and security, providing wireless coverage, real-time monitoring, remote sensing, and surveillance [1]. This leads to the necessity of teaching the development of UAVs at educational institutes.

The QNET 2.0 VTOL board Fig.1 (a) is a trainer (a prototype model of the drone) developed by Quanser which introduces vertical take-off and landing (VTOL) [2]. The QNET 2.0 VTOL board is specially designed for NI ELVIS II Fig.1 (b) and can be programmed in the LabVIEW environment.

Fig.1 (a). QNET 2.0 VTOL board

Fig.1 (b). QNET 2.0 VTOL board interfaced with NI ELVIS II

The built-in flight control model is simulated in LabVIEW and gains of the PID controller are adjusted manually to control the pitch angle of the QNET 2.0 VTOL board. The PID controller installed is manually tuned by adjusting the gains. This type of tuning requires an expert’s knowledge to perfectly tune the PID controller and requires a lot of time. The major problem occurs if the parameters change abruptly, then the system gets unstable. The PID controller is mainly used for linear systems whereas the VTOL is a nonlinear system. To overcome these issues an auto-tuned Fuzzy based PID controller is presented.

With the help of a comparative study of different controllers used to implement UAVs, it is suggested that fuzzy logic control proves to provide better results in comparison to other controllers [3, 4, 5, 6, 7, 8, 9, 10, 11]. A new auto-tuning method using Fuzzy logic is introduced for tuning of the PID controller on the QNET 2.0 VOL board in LabVIEW. An intelligent algorithm using Fuzzy logic is built, which is capable of auto-tuning the PID controller by using its gain parameters. This tuning method not only will control the pitch angle of the system efficiently but will also reduce the effort of manual tuning as it offers auto-tuning of the controller gain.

The proposed research’s main purpose is to control the pitch angle of QNET 2.0 VTOL. This research addresses the stabilization of the pitch angle of QNET 2.0 VTOL using a fuzzy-based tuning PID method. The main focuses of research include the study of QNET 2.0 VTOL model, design and implementation of fuzzy-based autotuned control logic to adjust intelligently the gain values i.e. K_p , K j and K_d for a stable pitch angle and finally, validate the results using fuzzy control and existing PID control.

The paper is arranged in the following sequence: the literature review is presented in section II. In section III methodology, the system is studied thoroughly and gain parameters, at which the system gets stable pitch angle are found. The system’s transfer function proves to help find out the gain parameters. Once the gain parameters are found then a fuzzy logic block is introduced in the system which takes in error and it's derivative as inputs and the gain parameters as outputs, which then are given to the PID controller. Based on these gain parameter values set of fuzzy rules are developed. Seven membership functions are chosen for all the inputs and outputs and their width is decided based on error and trial experience. Fuzzy blocks are built using these fuzzy rules. The fuzzy blocks replace the position control parameters block and introduce the auto-tuning of the controller gains. In section IV and V, the results are validated with the help of the system identification toolbox in MATLAB, which regenerates the response of the system.

• II.    Literature Review