Autonomous Control of a Quadcopter via Fuzzy Gain Scheduled PD Control Saad Sardar Electrical and Power Engineering Department Pakistan Navy Engineering College, NUST, Karachi, Pakistan saad_sardar12000@yahoo.com Muhammad Bilal Kadri Electrical and Power Engineering Department Pakistan Navy Engineering College, NUST, Karachi, Pakistan bilal.kadri@pnec.nust.edu.pk Abstract— This paper discusses the Intelligent Gain Scheduled PD technique to autonomously control the attitude of the Quad Copter. This paper would focus on two aspects of the autonomous quad-copter i.e. Attitude Control and Trajectory Following. The autonomous control of a quad-copter is a challenge due to its non-linear dynamics and environmental perturbations. The aim of the investigation is to study a Fuzzy Takagi-Sugeno method used to control the position and the yaw angle of the quad-copter and to compare the simulated results with the conventional PD Controller. Index Terms—Quadcopter, PD, fuzzy, gain-scheduling, Takagi-Sugeno I. INTRODUCTION The autonomous control of a quad-copter is a challenge due to its non-linear dynamics and environmental perturbations. The environmental perturbations can easily tip off the stability of the quad-copter since it has coupled EOM (Equations of Motion) which makes it easier for a disturbance to mitigate the effects of one of the rotors to other three. The non-linear dynamics of the quad-copter aggressively diminishes the performance of PD furthermore the spontaneous switching of the rotors can burn their motors. The aim of the investigation is to study about the different methods used to control the position and the yaw angle of the quad-copter. This investigation will be carried out using a complete Non-Linear Simulink model. We will discuss two control techniques i.e. (i) Gain Scheduled PD, (ii) Fuzzy Supervisory Gain Offset Mechanism/Capability to re-tune its parameters with the changing surroundings. Adaptive Gain-Scheduled control is a combination of classical and modern control approaches. This technique keeps the onboard computational requirements very low while the adaptation process regularly update the gains to counter perturbations thus increasing the robustness of the overall system. A. Literature Review • Adaptive Hybrid Control Algorithm Design for Attitude Stabilization of Quadrotor (UAV) This paper presents a new adaptive hybrid Fuzzy Logic based PID (FPID) Control algorithm for attitude stabilization of Quadrotor Unmanned Aerial Vehicle (UAV). Usually UAV systems are unstable and attitude stabilization control plays a very important role in it. The proposed algorithm for attitude controlling of UAV uses Fuzzy controller to online update the parameters of PID controller i.e. Kp, Ki and Kd that being used to control the attitude stabilization of quadrotor UAV. This approach acclimatizes the conventional PID Controller to a dynamic PID Controller. This new adaptive hybrid algorithm was simulated on MATLAB and compared with convention PID controller. Simulation results proves that proposed adaptive hybrid Fuzzy Logic based PID (FPID) controller give better results in the term of response time and settling time in quardroto UAV application as compare to convention PID controller. [1] • Control of a quadcopter using Self-Tuning Fuzzy PID Controller In this paper the modelling, simulation-based controller design and path planning of a quadrotor is discussed. An EKF based self-tuning Fuzzy PID control is proposed for the attitude control.to reduce the computational time a Dijkstra’s algorithm is used for path planning in a closed and known environment lled with obstacles and/or boundaries. The Dijkstra algorithm helps avoid obstacle and nd the shortest route from a given initial position to the nal position. [2] 12th International Conference on Frontiers of Information Technology 978-1-4799-7505-1/14 $31.00 © 2014 IEEE DOI 10.1109/FIT.2014.23 73 12th International Conference on Frontiers of Information Technology 978-1-4799-7505-1/14 $31.00 © 2014 IEEE DOI 10.1109/FIT.2014.23 73