液压外骨骼机器人非线性模糊滑模控制方法

Nonlinear Fuzzy SMC Algorithm for Hydraulic-driven Exoskeleton Robot System

针对液压外骨骼机器人系统建模困难的问题,提出一种利用自适应模糊逼近方法来实现对滑模等效控制的逼近,不需要对机器人的未知参数进行预先估计,同时设计可调参数的自适应调节律,增强系统的鲁棒性,引入一种类势能函数设计具有非线性积分项的滑模面,当误差较大时,积分效应适当减弱,防止产生较大的超调量;当误差较小时,积分效应适当增强,减小稳态误差。利用李雅普诺夫方法论证了该闭环控制系统的稳定性,并使用模糊切换方法来消除滑模控制抖振。最后,对液压助力外骨骼机器人系统进行轨迹跟踪及外干扰实验,结果验证了该方法的有效性,控制输出能快速平稳地跟随参考位置信号,且具有一定抗干扰能力。

In case of the difficulty in modeling for exoskeleton robot, an adaptive fuzzy logic control was presented to directly approximate the equivalent control without estimating the unknown parameters in advance. And an adaptive law in controller was designed to adjust its parameters according to parameter changes of the control system. In order to decrease the steady-state error and prevent from the integrator windup, a new nonlinear saturation function derived from quasi-natural potential function was designed to improve the performance of traditional integral sliding mode control. When the error beyond a boundary layer, the integral action was restricted by adjusting factor to avoid the large overshoot and long adjustment time. When the error was small, the integral action was completed so as to reduce the steady-state error and improve the robustness. The stability of the proposed controller was proved by using Lyapunov method. Furthermore, the chattering of sliding mode control was alleviated by simplifying the fuzzy control instead of switching function without deteriorating the system reliability and robustness. Finally, without acknowledging the model parameters of hydraulic-driven exoskeleton robot system, experiments were implemented to demonstrate the robustness and effectiveness of the method. And the results showed that the control output can follow the reference position signal quickly and smoothly with anti-interference ability.