基于迭代滑模的机械臂控制策略

Manipulator Control Strategy Based on Iterative Sliding Mode

针对机械臂这类非线性的不确定性系统,基于迭代学习控制与滑模控制策略,提出了一种有效的迭代滑模控制方法。该控制方法通过将滑模控制律引入到迭代学习控制中,并运用Lyapunov理论对控制律进行证明,从而确保系统的稳定性。基于拉格朗日力学法建立动力学模型,得到相对简化的n关节机械臂模型。以一个二关节机械臂为例,通过MATLAB仿真验证所提控制策略可有效提高关节的跟踪速度与跟踪精度,并且在一定程度上可减缓传统滑模控制的抖振现象,与传统迭代学习控制相比,系统具有鲁棒性。物理试验验证了所提控制策略的有效性。

An effective iterative sliding mode control(SMC)method based on iterative learning control and SMC strategy for such nonlinear uncertain systems as manipulator was proposed.The control method introduced the SMC law into the iterative learning control,and proved the control law by using Lyapunov theory to ensure the stability of the system.A relatively simplified n-joint manipulator model was obtained via the dynamics model which was established based on Lagrangian mechanics method.It was verified by a two-joint manipulator simulation on MATLAB that the proposed control strategy could effectively improve the tracking speed and tracking accuracy and alleviate the chattering phenomenon of the traditional SMC to a certain extent,and its robustness was better than the traditional iterative learning control.Finally,the effectiveness of the control strategy designed was verified by physical experiments.