板球系统遗传神经网络PID控制器参数优化研究

Research on Parameter Optimization of PID Controller by Using Genetic Neural Network for Ball and Plate System

板球系统是球杆系统的二维扩展,对其控制算法的研究可以提高实际系统的可靠性。板球系统作为典型的非线性、多变量控制系统,具有强耦合、欠驱动和无约束的特点。国内外学者对板球系统的研究主要在系统动力学分析和建模、视觉检测技术、小球定点控制与运动轨迹跟踪控制算法等方面。针对板球系统在传统RBF-PID控制中震荡大、精度低、实时性差等问题,应用拉格朗日方程对板球系统在忽略干扰因素的条件下进行数学建模,采用遗传算法优化PID参数;利用RBF神经网络具有逼近任意非线形函数的能力,在线调整PID参数;设计PID控制器,直接对被控对象闭环控制。在MATLAB环境下完成仿真,并在GPB2001型板球系统实物上完成定位控制和方形轨迹跟踪试验。试验结果表明,遗传神经网络控制算法能够提高板球系统定位控制、轨迹跟踪的稳定性和精度,对板球系统的控制效果有显著提高。

The ball and plate system is a two-dimensional extension of the ball-and-rod system.The research on its control algorithm can improve the reliability of actual system.As a typical non-linear and multi-variable control system,ball and plate system has the characteristics of strong coupling,under-actuated and unconstrained.Researches on ball and plate system conducted by domestic and foreign scholars mainly focus on system dynamics analysis and modeling,visual detection technology,small ball fixed-point control and motion trajectory tracking control algorithm.Aiming at the problems of large oscillation,low precision and poor real-time performance of ball and plate system in traditional RBF-PID control,Lagrange equation is applied to mathematically model ball and plate system under the condition of ignoring disturbance factors,genetic algorithm is used to optimize the PID parameters,and then RBF neural network is used to approximate any non-linear function and adjust the PID parameters online,and a PID controller is designed to directly closed-loop control the object.The simulation is completed in MATLAB environment,and the positioning control and square trajectory tracking experiments are completed on GPB2001 ball and plate system.The experimental results show that the genetic neural network control algorithm can improve the stability and accuracy of ball and plate system positioning control and trajectory tracking,and the control effect of ball and plate system is significantly improved.