The dynamic and digital real-time simulation of power system is believed as an indispensable tool for power system planning, protective and control devices designing and testing.
电力系统动态数字实时仿真已成为规划电力系统，设计与检验电力系统控制、保护以及调度设备的主要工具。
Proposed an adaptive network fuzzy inference system control strategy based on hierarchy structure of gait planning, which do not require detailed kinematics or dynamic biped models.
提出一种基于步态规划分级结构的自适应网络模糊推理系统控制策略，该方法不需要确定双足机器人运动学和动力学模型。
According to the time error, the yaw maneuvering command was generated and route dynamic planning on the basis of the pre-determined route was done to control the impact time.
在预定航路基础上利用时间误差信号生成侧向机动指令，通过航路动态规划，实现对攻击时间的控制。
This paper addresses time-invariant gait planning and finite-time nonlinear control strategy for a five-link, four-actuator planar biped robot to realize dynamic walking.
以五杆四驱动的平面双足步行机器人为对象，研究了其动态步行的时不变步态规划和限定时间的非线性控制策略。
In the question of on-line control for biped robot to step over dynamic obstacle, the learning time of footstep planning and gait pattern training is a crucial problem.
在双足机器人跨越动态障碍物的在线控制问题中，脚步规划和步态控制的学习时间是关键问题。
The dynamic characteristics and the stability of power systems need to be carefully considered in power system design, planning, and its operation and control.
电力系统的系统设计、规划、运行和调度需要充分考虑系统的动态性能及其运行稳定性，即需要对其机电暂态过程进行仿真。
Autonomous Underwater Vehicle (AUV) is an integrated system of multiple functions which include environment perception, dynamic decision, planning, control and implementation, etc.
无人潜航器(AUV)是一个集感知，决策与规划，控制与执行等多功能于一体的综合系统。
Autonomous Underwater Vehicle (AUV) is an integrated system of multiple functions which include environment perception, dynamic decision, planning, control and implementation, etc.
无人潜航器(AUV)是一个集感知，决策与规划，控制与执行等多功能于一体的综合系统。
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