有限值终态零化神经网络及其在机器人运动规划中的应用  

Finitely-valued Terminal Zeroing Neural Networks with Application to Robotic Motion Planning

作　　者：汪黎明 仲国民[1] 孙明轩[1] 何熊熊[1] WANG Liming;ZHONG Guomin;SUN Mingxuan;HE Xiongxiong(School of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)

机构地区：[1]浙江工业大学信息工程学院,杭州310023

出　　处：《计算机科学》2025年第5期270-280,共11页Computer Science

基　　金：国家自然科学基金(62073291,62222315)。

摘　　要：针对等式约束的时变二次规划求解问题,提出一种有限值终态零化神经网络,以保证计算误差的有限时间收敛,其有限值特性易于实现;对有限值终态零化神经网络进行理论分析,并给出该神经网络的收敛时间表达式。冗余机械臂的重复运动规划问题可描述为时变二次规划问题,采用有限值终态零化神经网络作为求解器,以获取末端执行器轨迹对应的关节轨迹。考虑到机械臂关节初始偏差难以避免,采用定参数/自适应参数的终态优化指标,在实现机械臂末端位置误差的有限时间收敛的同时,提高重复运动规划的精度。为保证机械臂的平稳运行,提出一种平滑修正的有限值函数用于终态优化指标设计。理论分析机械臂末端执行器位置误差的有限时间收敛条件。数值仿真以及UR5机械臂仿真与实验结果,验证了所提计算方案的有效性。To solve the problem of time-varying quadratic programming with equality constraints,this paper proposes a finitely-valued terminal zeroing neural network achieving the finite-time convergence of computing errors while being easy to implement.The convergence of the finitely-valued terminal zeroing neural network is theoretically analyzed,and the specific expression for settling time is provided.The repetitive motion planning problem of redundant robotic manipulators can be described as a time-varying quadratic programming.By employing the finitely-valued terminal zeroing neural network as a solver,the joint position and velocity trajectories,corresponding to the desired end-effector trajectory,can be obtained.Considering the inevitable initial joint shift,a terminal optimization criterion with fixed/adaptive parameters is proposed,aiming for finite-time convergence of end-effector position error and higher precision in repetitive motion planning.To ensure smooth operation of the robotic manipulator,a smooth-corrected finite-value function is proposed for the terminal optimization criterion,and the finite-time convergence of the end-effector position error is established.Numerical simulations and UR5 manipulator simulation and experimental results validate effectiveness of the proposed computing scheme.

关 键 词：终态零化神经网络 有限时间收敛 终态优化指标 冗余机械臂 自适应参数 重复运动规划 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]