Design And Optimization Of Attitude Control System For Quad-Rotor Aircraft Based On Improved Particle Swarm Optimization

Quad-rotor aircraft has the advantages of simple structure,convenient take-off and landing,high flexibility,which makes it exhibits a wide range of applications in the military and civilian fields.As a underactuated system with MIMO and nonlinearization,there is a coupling between each channel of quad-rotor aircraft.Meanwhile,the system itself is uncertain,and will suffer external interference more or less during actual flight.Thus,to maintain high accuracy and stability,it is very important to research flight control system of quad-rotor aircraft.This paper studies the attitude control of quad-rotor aircraft during hovering.The main work and innovation points of this paper are summarized as follows:(1)Aiming at the fixed-point hovering of the quad-rotor aircraft,a hover model of the quad-rotor aircraft is built according to the basic concept of controllability.A control capability index is defined to quantitatively analyse whether the zero point of the control quantity is an inner point of the constraint set.By calculating the control capability index to judge the controllability of the attitude for aircraft.(2)Due to the inherent defects of Inertial Measurement Unit,the individual solution of attitude angle has certain error.This paper proposes a variable gain compensation complementary filtering algorithm which estimates attitude angle with triaxial angle velocity measured by the gyroscope and calibrates the gyroscope by the accelerometer data.Meanwhile,this algorithm adjusts the parameters according to the motion state of the aircraft to achieve the optimal error compensation.Simulation and experimental results show that the proposed algorithm can effectively reduce the error in the attitude estimation.(3)This paper designs the attitude control system for a quad-rotor aircraft based on cascaded PID controller.Due to the coupling relationship between the attitude angles of the aircraft,it is difficult to obtain the optimal parameters of the controller by adjusting the parameters manually,which can only be performed separately for each controller.To obtain the optimal PID parameter group for the system dynamic performance,an improved particle swarm optimization is proposed to optimize all controller parameters simultaneously,which incorporates genetic operators and adopts a nonlinear decreasing inertial weight adjustment strategy.Simulation and experimental results demonstrate the effectiveness of the algorithm.