空间机器人随机故障容错规划的蜜蜂算法

本文为解决复杂的随机规划问题设计了一种基于随机模拟的混沌量子蜜蜂算法，证明了该算法的收敛 性，并分析了算法的收敛速度．分析6 自由度空间机器人系统的不确定性，采用基于微分变换法进行误差分析，建 立了随机数学规划模型．为涉及故障前后运动学与动力学约束限制的容错轨迹规划，以加权最小驱动力矩为优化性 能指标，采用混沌量子蜜蜂算法求解全部工作时间中机械臂故障前后的最优轨迹．通过降低异常关节的运动速度来 降低故障关节力矩，保证机械臂在发生故障后具有较高的操作能力．案例研究验证了该算法的有效性、稳定性及准 确性．

Fault Tolerance Trajectory Planning of Space Robot Subject to Stochastic Breakdown Using Honey Bee Algorithm

A stochastic simulation based chaos quantum honey bee algorithm(CQHBA)is designed for solving the complex stochastic programming problem.A proof of convergence is developed and the convergence speed of the algorithm is analyzed.Through analyzing the uncertainty and system errors of a 6 DOF space robot based on the differential transformation method,a stochastic mathematical model is built.To realize fault tolerance operation before and after the joint failures,the considerations on both kinematical and dynamical restrictions are taken into account.The optimal trajectory of the manipulator all along the work time before and after its joint failure is computed by CQHBA with minimal weighted driver torque as the performance optimization objective.Through lowering the motion velocity of the abnormal joint,the allowed torque of the abnormal joint is reduced.The algorithm guarantees that the manipulator has high manipulability after joint failure moment to accomplish its task successively,and lower the joint torque.A case study is presented to investigate the efficiency,stability and accuracy of the proposed algorithm.