Work place: Department of Electronic System Engineering, Mehran University of Engineering and Technology, Jamshoro, Sindh Pakistan
E-mail: arbab.nighat@faculty.muet.edu.pk
Website:
Research Interests: Computational Engineering, Engineering
Biography
Professor Dr. Arbab Nighat Kalhoro – She is working with the Department of Electronic Engineering, Mehran UET, Jamshoro, Sindh, Pakistan. She obtained her B.E in 1997 and M.E in 2009 from the Department of Electronic Engineering Mehran University of Engineering Technology Jamshoro. She completed her Ph.D. In 2004 from Beijing Institute of Technology (BIT), China. She has 26 national and international publications.
By Murk Junejo Arbab Nighat Kalhoro Arsha Kumari
DOI: https://doi.org/10.5815/ijitcs.2020.01.02, Pub. Date: 8 Feb. 2020
Unmanned aerial vehicles (UAVs) have gained a lot of attention from researchers due to their hovering and vertical take-off and landing. Different techniques and methods are being employed to imple-ment UAVs. The QNET 2.0 VTOL board, specially de-signed for NI ELVIS II, is an important platform in the field of unmanned aerial vehicles (UAV). It is a helpful tool to demonstrate the essentials of vertical take-off and landing flight control (VTOL) at educational institutes. The PID controller installed in QNET 2.0 VTOL board is manually tuned is usually done by a skilled operator. This process of tuning is time-consuming and requires an expert’s knowledge. Although PID control of various sys-tems has been reported in the literature, its use is limited in nonlinear systems. For nonlinear systems. Fuzzy logic is suitable due to its nonlinearity capability. The purpose of this research is to study the dynamics of the QNET 2.0 VTOL model, simulate the flight control model in Lab-VIEW and to design an auto-tuned PID controller using Fuzzy logic for QNET 2.0 VTOL model in LabVIEW environment. This study shows that Fuzzy based auto-tuned PID controller controls the pitch angle of the QNET 2.0 VTOL model and gives promising results as compared to the existing PID controller in terms of auto-tuning in real-time and stability of the system.
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