Research On Parameter Tuning Optimization Of The Controller Of The Ball And Plate System Based On Improved Particle Swarm Optimization

Traditional controller parameter setting is mainly through trial and error method.The designer continuously adjusts the controller parameters in real time based on his own experience and design system response,and finally finds a set of parameters that meet the design requirements.But the controller designed by trial and error method has long adjustment period,high labor cost and low efficiency.This paper selects the particle swarm algorithm of the intelligent algorithms and integrates it into the tuning of the controller parameters.In order to solve the problem of easy to fall into the local optimal solution in the process of particle swarm optimization,the inertia weight and learning factor that dynamically change with the number of particle iterations are introduced into the particle swarm optimization algorithm,which improves the optimization convergence accuracy and effectiveness.Then,using the ball and plate system as a carrier,the improved particle swarm optimization algorithm was used to simulate the controller parameter setting and the ball positioning experiment.The results show that the ball and plate system controller designed by the improved particle swarm optimization algorithm proposed in this paper achieves the steady-state control of the ball position,the control steady-state error is small,the effect speed is fast,and the feasibility of the method is verified.The content of this article is mainly divided into the following parts for research:The first part introduces the mechanical structure and related components of the ball and plate system,introduces the process of the balancing action of the ball and plate system and the working principle of the overall control of the ball and plate system;on this basis,consider the factors such as uncertain friction between the ball and the plate in the system as much as possible,use the Lagrange method to establish a more accurate and complete mathematical model for the ball and plate system,and then simplify the mathematical model according to the actual situation,and the Newton mechanics method was used to verify the mathematical model.The second part introduces the basic principle and algorithm optimization process of the basic particle swarm optimization algorithm and the complete particle swarm optimization algorithm with inertial weight,and briefly introduces the principles and the control system structure of PID,PD and PV controllers used in the ball and plate system.Because of its simple and easy structure,particle swarm optimization algorithm is widely used in function optimization by function research scholars.However,in the process of particle swarm optimization,there are usually shortcomings that it is easy to fall into local optimum and the effect of convergence accuracy is poor.In this paper,an improved particle swarm optimization algorithm is proposed.The inertial weights and learning factors that change with the dynamic curve of the number of particle iterations are introduced in the particle algorithm to improve the algorithm performance.The ITAE error criterion is selected as the fitness function of the algorithm function,and the proposed improved algorithm is applied to the controller parameter setting of the ball and plate system.The parameter tuning method of the ball and plate system controller is optimized,and the parameter tuning process of the ball and plate system controller based on the improved particle swarm optimization algorithm is introduced.In the third part,firstly,four test functions are selected to simulate the optimization performance of the improved particle swarm optimization algorithm proposed in this paper.The function test results show that the proposed improved algorithm has fast convergence speed,high convergence accuracy.It has good optimization effect.Secondly,a simulation model of the cricket system was established under the Simulink component of Matlab.Through the improved particle swarm algorithm implemented in Matlab,the ball and plate system simulation model in Simulink is called to realize the tuning of the parameters of the cricket system controller by the improved particle swarm algorithm.Through the simulation experiment and the ball positioning experiment carried out on ACROME's ball and plate system,the controller designed according to the improved particle swarm algorithm is tested.The results show that the improved particle swarm proposed in this paper is feasible and applicable to the parameter optimization method of the ball and plate system controller.