Trajectory Tracking of Nonlinear Unmanned Rotorcraft Based on Polytopic Modeling and State Feedback Control

Abstract

Trajectory tracking is extremely difficult for rotorcrafts based on the nonlinear model and taking into account all the parameters of the system and especially considering the effects of flapping and the main rotor and its control tail in all directions. This paper describes the tracking route, based on nonlinear model and velocity control and feedback mode and Polytopic linear parameter varying (LPV) modeling with the help of solving linear matrix inequalities (LMI) equations for different conditions and complex maneuvers for an unmanned rotorcraft that has been examined in all directions including, longitudinal, altitudinal, latitudinal directions. Based on the different operating points of the system and the different flight conditions, first a Polytopic modeling of the system is performed, and then the control signal is generated based on the state feedback and solution of the linear matrix inequalities (LMI) equations. The final control signal consists of feedback of changes of the state variables around the nominal trajectory under the designed feedback gains, in addition to the nominal control signal for the desired trajectory. In calculating the nominal control signal for the optimum trajectory, the Polytopic system model is used instead of the nonlinear system model. Therefore, the final control signal does not require a dynamic system model and all control calculations are performed using a Polytopic system model and have high computational speed. System simulation shows the capabilities of the proposed control system in different operating conditions.

KEYWORDS:

• Linear matrix inequalities
• LPV
• Nonlinear modeling
• Polytopic modeling
• Unmanned rotorcraft

Additional information

Notes on contributors

R. Tarighi

Reza Tarighi received his MSc degree in control engineering from the South Tehran Branch, Islamic Azad University, Tehran, Iran, in 2010. He is now a PhD student at South Tehran Branch, Islamic Azad University, Tehran, Iran. He has taught at the University of Applied Science and Technology Tehran from 2012. His current research interests include control analysis, robust control, WSN network and image processing. E-mail: [email protected]

A. H. Mazinan

Amir Hooshang Mazinan received the PhD degree in 2009 in control engineering. Dr Mazinan is the associate professor and also the director of the Control Engineering Department at Islamic Azad University, South Tehran Branch, Tehran, Iran, since 2009. He is now acting as the associate editor in Transactions of the Institute of Measurement and Control (Sage publisher) and Computers & Electrical Engineering Journal (Elsevier Publisher). Moreover, he is a member of the Editorial Board in three international journals and also a member of the programming committee in four international conferences. Dr Mazinan has more than 125 journal and conference papers published. His current research interests include intelligent systems, model-based predictive control, over-actuated space systems modeling and control, time-frequency representation, filter banks, wavelet theory, and image-video processing.

M.H. Kazemi

Mohammad Hossein Kazemi received his BSc degree in electrical engineering from the Khajeh Nasir University of Technology Tehran, Iran and MSc and PhD degrees in control engineering from the Sharif University of Technology, Tehran, Iran, and Amirkabir University, Tehran, Iran, in 1995 and 2001, respectively. He is currently an associate professor in the Department of Electrical Engineering in at the Shahed University, Tehran, Iran. His research interests include robotics, adaptive and robust control. E-mail: [email protected]