Research On Control And Parameter Optimization Of Cricket System Based On RBF

The ball and plate system is a multivariable,strong coupling and nonlinear control object,which is extended from the classical control object ball and beam system.In order to improve the response speed of the system and the control precision of the small ball trajectory of the ball and plate system,this paper designs and puts forward several optimization schemes of the ball and plate system based on the self-adaptive improved PID control of radial basis function(RBF)neural network from the angle of algor ithm optimization.First of all,this paper introduces the basic composition and working principle of the fixed height ball and plate system,analyzes the process of the small ball's movement caused by the force of the motor controlling the inclination ang le of the ball plate from the perspective of dynamics and energy conservation,and completes the qualitative analysis of the ball and plate system model combined with the advantages of Lagrange method in establishing the mathematical model.Due to the vari ability and strong coupling of the ball and plate system,the angle control model has higher control accuracy than the angular acceleration control model on the premise of ignoring the influence of light on camera image acquisition and energy loss caused b y friction between the ball plates.Therefore,the x-axis and y-axis motion of the ball and plate system can be divided into two parts Independent subsystem analysis.Secondly,aiming at the problems of the traditional PID control in the ball and plate system experiment,such as long control time and low accuracy of the ball trajectory,RBF neural network algorithm is combined with PID control to optimize the control ability of the ball and plate system.According to the characteristics of RBF neural network with good online optimization ability and nonlinear mapping,based on the established mathematical model,acceleration is introduced In order to improve the accuracy of RBF-PID control,Kalman filter algorithm(KF)is introduced and Kalman adaptive PID controller is designed;in order to optimize the tracking ability of RBF-PID control algorithm,LM(Levenberg Marquardt)algorithm is used to optimize the RBF-PID controller of ball and plate system,and the effectiveness of the improved algorithm in improving the self-tuning of system parameters is verified in Matlab environment capability and the feasibility of enhancing the robustness of the system.After the design of the controller,this paper uses the Gugao ball and plate system as the experimental platform,and sets up single and multiple fixed-point tracking control experiments and square trajectory tracking experiments respectively.Through the simulation and experimental verification of the algorithm before and after optimization,the results show t hat the control accuracy and convergence of the improved control algorithm are improved compared with the original algorithm,and it can be use.In order to reduce the adverse effects caused by the uncertainties of the strong coupling system,AR?RBF-PID has the best ability to improve the response speed of the system.RBF-PID algorithm can effectively remove process noise and measurement noise.The overall performance of RBF-PID control algorithm in the tracking control of the physical platform is the best.