机械臂非奇异快速终端滑模模糊控制

针对存在建模误差和外部干扰等大量不确定信息的机械臂轨迹追踪控制问题，提出带有自适应模糊系统的终端滑模控制方法. 该方法采用非奇异快速终端滑模面，使状态变量在滑动阶段具有全局快速收敛性；选取带有变系数的改进型双幂次趋近律，提高状态变量在趋近运动阶段的收敛速度，削弱控制器输出抖振；利用自适应多输入多输出（MIMO）模糊系统对系统模型以及外部干扰进行逼近，摆脱对具体模型信息的依赖，提高轨迹追踪精度和抗干扰能力. 通过构建Lyapunov函数证明系统的闭环稳定性和有限时间收敛性. 以Denso VP6242G串联机械臂为被控对象进行对比仿真和实验，结果表明所设计的控制器能有效提高轨迹追踪精度和抗扰动能力，并缓解控制器输出中的抖振现象.

Nonsingular fast terminal sliding model fuzzy control of robotic manipulators

A terminal sliding mode control method with adaptive fuzzy system was proposed for the robotic manipulator trajectory tracking control problem with a large amount of uncertain information such as modeling errors and external disturbances. The nonsingular terminal sliding surface was adopted to ensure global fast convergence of state variables during sliding stage in this method. An improved double exponential reaching law with variable coefficients was used to improve the convergence rates of state variables and suppress the chattering of controller output during the approaching stage. An adaptive fuzzy multiple-input multiple-output (MIMO) system was utilized to approximate the system model and external disturbance, in order to get rid of the dependence on model information and improve trajectory tracking accuracy as well as anti-disturbance performance. The closed-loop stability and finite-time convergence of the system were proved by constructing Lyapunov functions. The Denso VP6242G serial manipulator was taken as the controlled object for comparative simulation and experiment. Results showed that the designed controller can effectively improve the trajectory tracking accuracy and anti-disturbance ability, and alleviate the chattering phenomenon in the controller output as well.