Genetic Algorithm Based on Analytic Hierarchy Process PID Parameter Tuning of UAV Control System

The control problems of quad-rotor flight such as under-actuated control, strong coupling were analyzed. With a simplified dynamic model of quad-rotor based on Newton Euler equation, a double-loop PID controller which consists of the inner attitude control and out position control. Ac cording to the requirements such as static characteristics, dynamic performance and reliability, the s ystem is divided into the system layer, subsystem layer and parameters layer. Aiming the multi-objective optimization index, the method of analytic hierarchy genetic algorithm was used for PID parameters determining. Then outdoor flight experiments were conducted with the controller and parameters obtained. The experimental results show that the aircraft can meet the engineering accuracy requirement of an outdoor flight. Introduction The growing interest for the aerial robotics research community in unmanned aerial vehicles (UAV) as exemplified by helicopters [1~4]. Multi-copter is due to the applications in both military scenarios and civil that can be equipped with other sensors to explore building, collect information and investigate dangerous environments. For the reason that light structure, small size, low cost, takeoff and landing model and flexible flight ability, quad-copter research has drawn greater attention. UAV control system is the core technology of the quad-copter system. Several designs about quad-copter control system in the world, showed in many research papers [5~7]. To realize accurate performance and high dynamic performance, simple, robust and intelligent control laws are introduced in designing the quad-copter control system, for instance, sliding model control, Neural network control, back-step control. Genetic algorithm (GA) is a kind of intelligent computational model, simulating nature evolutionary mechanism, based on Darwinian Evolution idea. The algorithm starts from random or specific initial solution sets, follows iterative computation logic, such as selection, crossover and mutation operator, calculates and updates new solution set. Based on fittest survive principle, GA leads research result to the optimal solution. Since in nature, fittest individuals dominating over the weaker ones. A two closed loop PID control system, composed with inner attitude control loop and outer position control loop, using GA to resolve multi-objective optimization problem in control loops is presented in the paper. The control system is applied in an experimental quad-copter, a serial experiment results verify the effectiveness of the proposed algorithm. Dynamics Model Coordinate build For the purpose of conveniently describe and dynamics model, the coordinate system is built as Fig.1, body coordinate system and earth coordinate system. Original point of the body coordinate system is set in the center mass of UAV. X-axis is along the vehicles head, Z-axis is at 90° to the ground, Y-axis is settled following right-hand rule. The two coordinates are overlap completely until the quad-copter takeoff, the earth one is considered as inertial coordinate system, does not change in the UAV flight model. Quad-copter has six degrees of freedom in three-dimensional space. Rotation transfer matrix R is given by: 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) © 2016. The authors Published by Atlantis Press 1340