本文考察带动力学不确定性的刚性机械臂的跟踪控制问题。
The problem of tracking control for a rigid robot manipulator with uncertainties in its dynamics is considered in this paper.
本文分析了轮式移动机器人在运行过程中由于动力学不确定性引起的力矩扰动，并提出了一种基于传感器的移动机器人控制方法。
This paper analyzes the torque disturbance of the wheeled mobile robot due to dynamic uncertainties during motion and presents a sensor based control method for the mobile robot.
由于可重构机械臂的动力学系统中存在大量的不确定性，导致PID等传统的控制器无法实现精确的位置控制。
There are many uncertainties in real dynamic system of reconfigurable manipulator that make PID type or traditional control methods unable to realize accurate position control.
该控制器由三部分组成：线性PD反馈项，补偿动力学的自适应控制项，补偿建模不确定性的鲁棒控制项。
The controller consists of a linear PD feedback part, a nonlinear adaptive feedback part to compensate for the dynamics of robot and a robust control part to compensate for the uncertainties of model.
由于自主水下航行器建模误差、流体动力学参数的不确定性和未知海流干扰，控制系统必须具有对不确定参数的自适应能力。
The control system must be adaptive to the uncertain parameters to overcome the modeling error, uncertainty of the hydrodynamic parameters and unknown ware disturbances.
针对机器人动力学模型的不确定性和负载扰动，提出了一种采用神经网络的机器人迭代学习控制方法。
Aiming at dynamic model uncertainties and load disturbances of robot manipulators, an iterative learning control scheme using neural networks is presented.
由于柔性机械手具有复杂的动力学模型，因此不可避免存在参数不确定性和未建模动态。
There inevitably exist the parametric uncertainty and unstructured uncertainty due to the complex dynamics of flexible-link manipulators.
针对汽车方向动力学控制存在的非线性和参数时变不确定性问题，提出了一种新的基于单神经元的汽车方向自适应pid控制算法。
In view of the nonlinearity and parameter time-varying uncertainty of vehicle dynamics, a novel algorithm, i. e. single neural adaptive PID control strategy, is propsed for vehicle direction control.
用自适应过程减小参数不确定性的影响，并通过动态滑模控制器的高鲁棒性抑制机器人模型中的未知非线性动力学及测量噪声等的影响。
The adaptive process extenuates the influence of parameter uncertainty, and the robustness of the dynamic sliding mode control inhibits the influence of unknown dynamics and measurement noise.
建立了可控约束阻尼层悬臂梁的动力学模型，分析了模型中的不确定性。
The modelling problem for a cantilever beam with a controllable constrained damping layer is discussed in detail.
这些不确定性可以归结为对动力学系统运动方程序的摄动。
The uncertainty may be solved by the perturbation method to the motion equations of the dynamic system.
之后又做了基于动力学模型的滑模变结构控制仿真，发现变结构仿真在处理模型的不精确性和不确定性方面有良好的效果。
In the dynamic modeling and control simulation, first , the the dynamic model of the macro-mechanism using Kane methods was built and dynamic simulation using matlab was carried out.
之后又做了基于动力学模型的滑模变结构控制仿真，发现变结构仿真在处理模型的不精确性和不确定性方面有良好的效果。
In the dynamic modeling and control simulation, first , the the dynamic model of the macro-mechanism using Kane methods was built and dynamic simulation using matlab was carried out.
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