基于操纵子学模型的5自由度宏-微精密机械手运动的映射关系

Control System of Five Degrees of Freedom of Macro- micro Precision Manipulator Based on Operon Model Mapping

针对宏-微机械手末端位姿、位置准确度的误差问题,受细胞学操纵子学说的启发,提出了基于操纵子模型的宏-微精密机械手运动的映射关系,研究精密机械手运动的影响因子和细胞学中的操纵子模型,分析机械手精密运动影响因子的影响方式和操纵子模型的结构组成及其工作机理,结合操纵子模型的工作机理,分析宏-微机械手的控制系统,在此基础上,求解机械手精密运动控制系统的操纵子模型,考虑在几何因素的影响下,得出机械手末端位置在影响因子前后的误差值,通过基于粒子群算法的比例-积分-微分(Proportional-integral-differential,PID)控制器对误差结果进行优化,得出基于时间乘绝对误差积分准则(Time multiplied by the absolute error integral,ITAE)的粒子群算法(Particle swarm optimization,PSO)变化曲线和PID最优的控制参数。结论表明由映射关系推导出的控制系统能够满足一定的精度要求,并能进一步提高机械手的运动精度,为生物控制在机器人中进一步的创新研究提供了理论基础和依据。

For the error problem of the position and the location in the process of operation of macro- micro manipulators, inspired by cytology said manipulation behavior, the control system based on operon mapping relationships in the cause of the mechanical precision is put forward, used to study the effect of mechanical precision movement factor and the operon model in cytology, the effect of the factor of the impact on mechanical precision motion and the structure of the operon model and its working mechanism, within the impact of these factors, the mapping relationship between factors influencing the precision of manipulator is established, the degree of the influence is put out, the macro- control system of micro manipulator is analyzed, the mapping relationship between the manipulator operon model based on the control system is solved, considering the influence of the geometric factors,the error of the simulation model is obtained, the result of error is optimized by the proportional-integral-differential（PID） controller based on particle swarm algorithm, the time multiplied by the absolute error integral（ITAE） performance index curve and the control parameters of PID optimized by the particle swarm optimization（PSO） are obtained, the conclusion that the mapping relation can satisfy a certain accuracy requirement is indicated, and the precision of the manipulator movement can be further improved, thus providing the theoretical basis for the further innovation research on the biological control of robots.