Comparative of Ziegler Nichols, Fuzzy Logic and Extremum Seeking Based Proportional Integral Derivative Controller for Quadcopter Unmanned Aerial Vehicle Stability Control
Unmanned aerial vehicle is potentially recognized in autonomous sectors where intelligence gathering, surveillance, reconnaissance missions, power line inspection, aerial video, search and rescue monitoring devices are required. It is essential in modern era control and monitoring especially a rotary unit where quadcopter performed a crucial task. However, the flight behavior of a quadcopter is determined by the synchronous speed of each of the motors as the speed changes with load torque variations. The dynamics model equation of the system, external disturbances and its parameters variation of the motor makes it difficult for the manual tuning techniques employed into the system to perform its stability operation. The purpose of this work is to employ adaptive controllers to enhance the stability performance so as to prevent the risk of human lives and financial implication that may arise from improper monitoring of the system. Therefore, Ziegler Nichols, fuzzy logic and extremum seeking controllers were employed to auto-tuned the parameters of proportional integral derivative (PID) gains controller to optimize and give a satisfactory performance of motor speed control at different operating condition. The altitude, pitch, roll and yaw parameters of the quadcopter are simulated using the x-plane II flight simulator MATLAB tools. The simulation results presented in this work show better performance for extremum seeking-PID in terms of decrease in rise time, settling time and overshoot relative to Zigler-Nichols-PID and Fuzzy-PID controllers.
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