$\mathscr{L}_{1}$ Adaptive Control Design Using CMPC: Applied to Single-Link Flexible Joint Manipulator

Hossein Ahmadian, H. Talebi, I. Sharifi
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Abstract

Controlling flexible robots is a challenging issue for a variety of reasons, including: highly nonlinear dynamics, strong coupling, time-varying specifications, vibration and deviation. In addition, the existence of dependent uncertainties on their dynamics and kinematics is inevitable, so that accurate models for controller design are not available in such systems. In this paper, one “$\mathscr{L}_{1}$ adaptive controller $({\mathscr{L}_{1}}\_{\text{AC}})$” using “continuous-time model predictive control (CMPC)” is proposed on position tracking and removing vibration and deviation in “single-link flexible joint manipulator (SLFJM)” with existence of the unknown nonlinear dynamics and uncertainties. Eventually, in order to evaluate the efficiency of the proposed method, this method is simulated on SLFJM and the results are compared with conventional ${\mathscr{L}_{1}}\_{\text{AC}}$ and “Model Reference Adaptive Control (MRAC)” methods.
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$\mathscr{L}_{1}$基于CMPC的自适应控制设计:应用于单连杆柔性关节机械手
由于各种原因,包括高度非线性动力学、强耦合、时变规格、振动和偏差,柔性机器人的控制是一个具有挑战性的问题。此外,由于其动力学和运动学上不可避免地存在依赖的不确定性,因此在此类系统中无法获得用于控制器设计的精确模型。针对存在未知非线性动力学和不确定性的“单连杆柔性关节机械臂(SLFJM)”,提出了一种采用“连续时间模型预测控制(CMPC)”的“$\mathscr{L}_{1}”$自适应控制器$({\mathscr{L}_{1}}\_ \text{AC}})$”。最后,为了评估该方法的有效性,在SLFJM上进行了仿真,并将仿真结果与传统的${\mathscr{L}_{1}}\_{\text{AC}}$和“模型参考自适应控制(MRAC)”方法进行了比较。
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