Quadrotor UAV Position and Altitude Tracking Using an Optimized Fuzzy-Sliding Mode Control

Abstract

Quadrotors are one of the Unmanned Aerial Vehicles (UAVs) that have many applications in the aerospace industries which require a high level of accuracy and innovation in control and stability. In this paper, a hybrid control structure is proposed for this system. The sliding mode controller (SMC) is the foundation of this control structure. This controller, despite its high stability capability for nonlinear systems, has two weaknesses: chattering phenomenon and high vulnerability to noise. The proposed solution is to incorporate the SMC and the Fuzzy intelligent controller because of its high flexibility against the changes in the system model conditions. The new Fuzzy-SMC resolves the SMC weaknesses significantly, but it is not optimized due to a lack of access to the system model expert information. In order to optimize the Fuzzy-SMC, it is necessary to have accurate structural information and specification of the system model which are not available for this case. The final proposed solution is to synthesize the Genetic Algorithm (GA) with the Fuzzy-SMC. In GA performance, each Fuzzy rule is regarded as a chromosome and at each stage, the best of chromosomes, containing the fastest responding, are passed on to the next generation as the elite. The rest combine to create the next generation by using combination and mutation methods. Thus, the Fuzzy-SMC operates based on optimized Fuzzy rules. The results of the simulation in MATLAB software clearly show that the state of quadrotor reaches the desired value and location at the appropriate time.

KEYWORDS:

• Chattering phenomenon
• Fuzzy intelligent controller
• Fuzzy-SMC optimized by genetic algorithm
• Quadrotor robot
• Sliding mode control
• Unmanned aerial vehicles

Additional information

Notes on contributors

Mohammadhossein Zare

Mohammadhossein Zare received his BSc degree in mechanical engineering from Tehran Central Branch and his MSc degree in aerospace engineering from Science and Research Branch, both Islamic Azad University, Tehran, Iran, respectively, in 2008 and 2014. He is currently a PhD candidate under the supervision of Dr Farshad Pazooki at Science and Research Branch, Islamic Azad University, Tehran, Iran. His research interests include flight dynamics and control, robotics, and control of unmanned aerial robots focused on nonlinear control systems, intelligent control, and fuzzy logic. Email: [email protected]

Farshad Pazooki

Farshad Pazooki received his PhD degree in aerospace engineering from Science and Research Branch, Islamic Azad University in 2008. He is currently an assistant professor in the faculty of Aerospace Engineering at Science and Research Branch, Islamic Azad University, Tehran, Iran. His research interests include aircraft design, applied optimal control, optimal trajectory design and analysis of aerospace vehicles.

Shahram Etemadi Haghighi

Shahram Etemadi Haghighi received his MS and PhD degrees in mechanical engineering from Sharif University of Technology, Tehran, Iran, respectively, in 2003 and 2011. He is currently assistant professor of Department of Mechanical Engineering at Science and Research Branch, Islamic Azad University, Tehran, Iran. His studies are in the field of nonlinear vibration and control and he is interested in swarm robotics and flapping wing robots. Email: [email protected]