基于广义双曲正切模型的机器人鲁棒模糊自适应控制

利用广义模糊双曲正切模型的全局逼近特点,设计一种模糊自适应控制器用于机器人轨迹跟踪控制.广义双曲正切模型利用输入变量的平移能以任意精度逼近系统的不确定动态.对于系统不确定外界干扰和模糊系统的逼近误差,通过求解一个线性矩阵不等式来保证闭环系统的鲁棒稳定性.对比传统的模糊基函数,在保证系统跟踪精度的前提下,双曲正切模糊基函数的自适应调整参数大大减少,仿真表明该控制算法具有较强的鲁棒性能和较好的跟踪性能.

Robust fuzzy adaptive control of manipulators based on the generalized hyperbolic model

Taking advantage of the property of the generalized hyperbolic model:a universal approximator,a fuzzy adaptive controller is proposed for the trajectory tracking control of robotic manipulator.Firstly,by translating the input variables,a generalized hyperbolic model can approximate to any uncertain dynamics by an arbitrary accuracy.For the external disturbances and the approximation errors,a linear matrix inequality(LMI) problem is then solved to guarantee the robustness of the closed-loop.Being different from the traditional fuzzy-based function,the hyperbolic model uses fewer updated parameters to guarantee a satisfactory tracking performance.Finally,numerical simulations are carried out to show the expected robustness and tracking accuracy.