Research On High-performance Control Method Of Global Launch Platform Based On Interference Compensation

As the application of the all-terrain launching platform becomes more and more widespread,the requirements for the control performance of the all-terrain launching platform are also getting higher and higher.Since the all-terrain launching platform has the characteristics of parameter uncertainty and other uncertain nonlinearities,how to eliminate the impact of these non-linear factors is the key to improving control performance.Aiming at how to eliminate the influence of non-linear factors,the main works of this paper are focused as follows:1.The structure features of the all-terrain launching platform are introduced,and the tricyclic transfer function of the motor servo system is analyzed and established.In addition,the coupling disturbance characteristics of the all-terrain launching platform are analyzed,and then establish the two-axis coupling cdynamics model.2.Combined with BP neural network and PID control,the neural network supervisory controller is designed.Utilize the self-learning ability of neural network to improve the self-adaptive ability and the stable tracking accuracy of the controller.Simulation results show that neural network supervisory control could not only obtain the rapid response capability of the system,but also improve the adaptability and stability of the controller.3.Based on the dynamic model of the two-axis coupling of the all-terrain launching platform,the RBF neural network based adaptive robust controller is designed.The system parameters can be adjusted online using the parameter adaptation rate,the RBF neural network can be used to estimate the uncertain nonlinearity of the system and compensated in and feed-forward term,which improves the anti-interference ability and stability tracking accuracy of the system.The simulation results show that the RBF neural network based adaptive robust controller can reduce the influence of system uncertainty on the system effectively.4.The hardware circuit and software programming of position controller based on DSP F2812 are achieved,and the control algorithm is transplanted to the position controller for experiment.The experimental results verify that neural network supervisory controller and neural network-based adaptive robust controller could obtain good control performance,providing the reference for improving the performance of the launching platform.