基于遗传算法优化的机械臂动态矩阵预测控制

Dynamic Matrix Predictive Control of Manipulators Based on Genetic Algorithms

动态矩阵预测控制(dynamic matrix predictive control,DMC)作为线性系统过程控制的一种常用方法,其控制效果受其控制权矩阵等参数影响较大。针对DMC算法控制权参数矩阵离线调参问题,根据控制系统输入、输出参数设计适应度函数,提出了一种基于遗传算法优化的DMC方法,以单关节机械臂作为被控对象,设计了DMC控制系统来进行控制对象单位阶跃响应采样以及遗传算法离线调参,并用该控制系统以及遗传算法所得参数进行仿真验证。结果表明,通过遗传算法可快速、精准地获得具有较优输出效果的DMC算法控制权参数矩阵,为采用DMC进行机械臂控制提供了便利。

Dynamic matrix predictive control(DMC)was a common method for process control of linear systems.The control effect of this method was greatly affected by the parameters of its control matrix.Aiming at the off-line parameters adjustment,an augmented DMC method was presented in this paper as well as fitness function based on input and output parameters of control system was designed.With a single-joint manipulator as the controlled object,a DMC control system was designed to sample the unit step response of the controlled object and the parameters of its control matrix were adjusted offline by genetic algorithm.Simulation verification was performed using the parameters of the system and the genetic algorithm then.The results showed that the parameters of control matrix of DMC algorithm with better output could be obtained quickly and accurately after optimized using genetic algorithm,which made convenience for using DMC for manipulator control.