改进非线性干扰观测器的机械臂自适应反演滑模控制

针对传统滑模和传统干扰观测器在机械臂关节位置跟踪中存在的控制输入抖振、需要测量加速度项、应用模型受限等问题，提出一种改进非线性干扰观测器的机械臂自适应反演滑模控制算法。首先，设计改进的非线性干扰观测器进行在线测试，在滑模控制律中加入干扰估计值对可观测的干扰进行补偿；然后选择合适的设计参数，使观测误差指数型收敛；其次，引入反演自适应控制律，对不可观测的干扰进行估计，进一步改善控制系统的跟踪性能；最后，利用李雅普诺夫函数验证了闭环系统的渐近稳定性，并将其应用于机械臂关节位置跟踪。实验结果表明，与传统滑模算法比较，所提控制算法不但加快了系统的响应速度，而且能有效地削弱系统抖振、避免测量加速度项并扩大应用模型使用范围。

Adaptive backstepping sliding mode control for robotic manipulator with the improved nonlinear disturbance observer

In order to solve the problems of control input chattering of traditional sliding mode, requiring acceleration term, and limited application model of traditional disturbance observes in manipulator joint position tracking, a self-adaptive inverse sliding mode control algorithm for manipulators with improved nonlinear disturbance observer was proposed. Firstly, an improved nonlinear disturbance observer to perform on-line testing was designed. In the sliding mode control law, interference estimates were added to compensate for observable disturbance, and then appropriate design parameters were selected to make the observation error converge exponentially; the adaptive control law was performed to estimate the unobservable interference and further improved the tracking performance of the control system. Finally, the Lyapunov function was used to verify the asymptotic stability of the closed-loop system, then the system was applied to the joint position tracking of the manipulator. The experimental results show that compared with the traditional sliding mode algorithm, the improved control algorithm not only accelerates the response speed of the system, but also effectively suppresses the system chattering, avoids measuring acceleration items and expands the application scope of the application model.