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通过对机器人的运动轨迹准确跟踪控制,能够有效提高机器人路径规划和自主定位的准确性。机器人在运动过程中运动轨迹受到小扰动分段线性误差的影响,机器人系统是一个多变量非线性系统,传统的遗传算法进行运动轨迹跟踪控制在边界层出现稳态跟踪误差。针对以上问题提出一种基于改进遗传算法的机器人运动轨迹跟踪控制算法。模拟构建所研究的机器人的运动环境模型,把机器人运动轨迹的空间坐标抽象为遗传种群的虚拟世界,得到机器人运动空间的网格结构模型。通过遗传进化的方式寻找目标点并进行移动,为了使得机器人的运动轨迹控制满足遗传算法的匹配条件和参数摄动带来的误差,在机器人运动轨迹滑膜面设计一个跟踪误差的积分项,实现算法改进。仿真结果表明:采用该算法进行机器人运动轨迹控制,能以较快的收敛速度找到最优路径,机器人跟踪控制性能精确度和收敛性较好,性能优越。
Accurate tracking and control of robot trajectory can effectively improve the accuracy of robot path planning and autonomous positioning. The trajectory of the robot is affected by the piecewise linear error of small perturbation during the movement. The robot system is a multivariable nonlinear system. The traditional genetic algorithm tracking control of the trajectory appears steady-state tracking error in the boundary layer. Aiming at the above problems, this paper proposes a tracking control algorithm for robot trajectory based on improved genetic algorithm. The motion environment model of robot is simulated and the space coordinate of robot trajectory is abstracted as the virtual world of genetic population to get the grid structure model of robot motion space. In order to find the target point and move it by genetic evolution, in order to make the robot’s trajectory control meet the genetic algorithm’s matching condition and the parameter perturbation error, an integral term of tracking error is designed on the synovial plane of robot trajectory Algorithm improvement. The simulation results show that the proposed algorithm can find the optimal path with faster convergence speed by using the proposed algorithm. The accuracy and convergence of robot tracking control are better and the performance is superior.