The sliding mode dynamics is regular, impulse-free and asymptotically stable.
滑模运动正则、无脉冲模、渐近稳定。
Valid dynamic sliding mode output that guarantees the system stable zero dynamics was constructed, and a global second order sliding mode control was adopted to circumvent chattering phenomena.
通过构造动态滑模输出，使得系统零动态稳定；采用全局二阶滑模控制来消除抖振。
First, according to the tracking error dynamics and kinematics described by unit quaternion error and angular velocity error, a sliding mode controller is derived based on Lyapunov theory.
首先根据由误差四元数和误差角速度描述的跟踪误差动力学和运动学方程，设计了基于李亚普诺夫方法的滑模变结构控制律。
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.
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 concept of the finite time sliding mode is introduced in which the advantage is that the linear dynamics tend to zero in finite time.
引入了有限时间滑动模态的概念，其优点是线性部分的状态在有限时间内趋近于零。
A control law, that constrains the state to follow the sliding mode in the state space, is designed on the basis of a nonlinear, simplified model of the completely liquid-filled spacecraft dynamics.
基于充液飞行器的简化模型，在状态空间中设计控制规律以约束状态至滑模。滑模通过在一个约化空间中求解最优控制问题获得，其解是角速度作为姿态变量的函数。
After that, many control algorithms are studied based on dynamics analysis and model foundation, then the intelligent fuzzy sliding mode controller is proposed and designed.
接着，在对并联机构进行动力学分析和建模的基础上，研究了多种控制算法，最终提出并设计了智能模糊滑模控制器。
RBF neural network is proposed to approximate unknown nonlinear function. Sliding mode error is used to adaptively tune its weights online. Dynamics performance is improved.
采用RBF神经网络逼近系统未知的非线性函数，引入滑模误差对其权值进行在线自适应调整，改善动态性能。
RBF neural network is proposed to approximate unknown nonlinear function. Sliding mode error is used to adaptively tune its weights online. Dynamics performance is improved.
采用RBF神经网络逼近系统未知的非线性函数，引入滑模误差对其权值进行在线自适应调整，改善动态性能。
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