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Time-optimal control of robotic manipulators with uncertain dynamics and constraints

机译:具有不确定动力学和约束的机器人操纵器的时间最佳控制

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The issues of the development of a nonlinear mathematical model and robust time-optimal control of rigid-link robotic manipulators are addressed. Constraints, nonlinearities and uncertainties, of manipulators and electric motors affect the performance characteristics of robotic systems and should be studied in detail. The nonlinear dynamical model of manipulators actuated by DC motors is derived on the basis of the Euler-Lagrange formulation. The constraints represent physical and kinematical bounds of mechanical components and electric motors. In this paper, the robust control issues for manipulators are investigated using the Hamilton-Jacobi theory. For robotic systems with unknown but bounded parameters and constraints on the state variables and control inputs we develop the robust time-optimal control strategy. A procedure for designing the robust bang-bang controllers is given and the nonquadratic performance measure is minimized. The proposed control methodology is feasible, reliable and provides the computational efficiency. The first joint of a manipulator with permanent-magnet DC motor is studied to demonstrate the efficiency of the robust control procedure and the bang-bang control algorithm. Experimental results are presented to verify the robustness and dynamic performance.
机译:解决了非线性数学模型的发展问题和对刚性连杆机器人操纵器的鲁棒时间最佳控制。机械手和电动机的约束,非线性和不确定性影响机器人系统的性能特征,并应详细研究。由DC电机致动的机械手的非线性动力学模型是基于欧拉拉格朗日配方推导出来的。约束代表机械部件和电动机的物理和运动界。在本文中,使用Hamilton-Jacobi理论研究了操纵者的强大控制问题。对于具有未知但有界参数的机器人系统和状态变量和控制输入的约束,我们开发了强大的时间最优控制策略。给出了设计强大的Bang-BANG控制器的程序,并且无数型性能测量最小化。所提出的控制方法是可行,可靠的,提供计算效率。研究了具有永磁直流电动机的机械手的第一接合,以展示鲁棒控制程序和Bang-Bang控制算法的效率。提出了实验结果以验证鲁棒性和动态性能。

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