Research On Model Predictive Control Methods For Three Degree Of Freedom Helicopter With Uncertainty

Helicopter plays an important role in national economy and people's life,which has made tremendous contributions for the development of science and technology and social progress."CH47-Chinook" is an excellent helicopter for transport performance and it could carry some large and overweight equipment.In order to study a variety of problems of this type of helicopter during the flight,Quanser company of Canada produces the three degree of freedom(3DOF)helicopter model,which is a simplified simulation of the "CH47-Chinook" helicopter.The characteristics of the model can be summarized as high order,unstable,multivariable,nonlinear,strong coupling and time varying.Facing such complex system,traditional control method becomes somewhat helpless.Whereas the model predictive control(MPC)can solve the input and output constraints of plant using direct method with good robustness and control effect.Therefore,in this paper,we focus on the attitude tracking problems of the 3DOF helicopter based on MPC.The helicopter will encounter a variety of external disturbances in the actual flight,resulting in uncertainty in the progress of flight control.At the same time,the dynamic characteristics of the 3DOF helicopter system are changed with the flight height and attitude and could lead to the change of structure and parameters of plant,which are usually difficult to be described by the precise mechanism model.If not consider these uncertain factors in the process of designing helicopter flight controller,it will cause model mismatch and affect the performance of attitude tracking.So,in this paper we will focus on the problems of disturbances and uncertainty problems of model in the process of flight control of the 3DOF helicopter.Main research contents of this paper are as follows:(1)For the problem of unknown outside disturbances,nonlinear mechanism model of 3DOF helicopter is linearized at each sampling time.And the disturbance observer is used to estimate disturbances.Then we design the model predictive control based on disturbance prediction and without disturbance prediction respectively,and an optimal solution is obtained using a simple dual network(SDN).Finally,in the simulation,the proposed method is carried out to verify the effectiveness of the proposed method.(2)For the problem of uncertainty of 3DOF helicopter model,the stability controller and the multisine excitation signals of the 3DOF helicopter model are designed.Then,the closed-loop identification of the system is performed by using the echo state network(ESN).Based on the obtained ESN model,the model predictive controller is designed.An optimal solution with input and output constraints is obtained using a SDN.Finally,a experiment is carried out to verify the effectiveness of the proposed method in 3DOF helicopter attitude control.