基于模糊控制系统的机械臂自适应控制算法设计

针对现有机械臂控制算法,在轨迹控制和精度补偿方面存在的不足,设计了一种基于模糊补偿系统的自适应控制算法。先在笛卡尔空间内分析了机械臂的空间动力学运动过程,并得出机械臂运动中的最优力矩值,构建模糊控制规则并设定模糊子集；对经典模糊理论进行优化,引入可变论域思维在机械臂运动过程中,系统会实时反馈末端执行器行动轨迹,并实施动态化补偿；基于自适应算法对可变论域模糊控制器进行二次优化,修正模糊规则并校正模型的控制量参数,提升和改善整个机械臂系统的控制精度。实验结果显示,模糊补充自适应控制算法在多关节和多连杆机械臂的角度控制和位移控制精度方面有较大的优势,同时各关节和连杆的运动相应时间仅为0.27s和0.20s。

Design of Adaptive Control Algorithm for Manipulator Based on Fuzzy Compensation System

An adaptive control algorithm based on fuzzy compensation system is designed to overcome the shortcomings of the existing control algorithms in trajectory control and precision compensation. Firstly, the space dynamic motion process of the manipulator is analyzed in Cartesian space, and the optimal torque value is obtained. The fuzzy control rules are constructed and fuzzy subsets are set. The classical fuzzy theory is optimized, and the variable theory domain thinking is introduced. During the movement of the manipulator, the system will feedback the action trajectory of the end actuator in real time and implement dynamic compensation. Based on the adaptive algorithm, the quadratic optimization of the variable theory domain fuzzy controller is carried out, the fuzzy rules are corrected and the control parameters of the model are corrected, and the control accuracy of the whole manipulator system is improved. The experimental results show that the fuzzy supplementary adaptive control algorithm has great advantages in the Angle control and displacement control accuracy of multi-joint and multi-link manipulator, and the corresponding motion time of each joint and link is only 0.27s and 0.20s.