Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Multi-input and Multi-variable systems
Feedback control systems
Reinforcement Schedules
Linear Approximation in Time Domain
Distributed Loads: Problem Solving
您也可能阅读
通过共同作者、期刊和引用图与本文相关的文章。
本研究介绍了一种无模型的强化学习 (RL) 方法,用于在非线性多代理系统中实现最佳的共识控制. 它有效地处理输入约束和分布式同步挑战,使用关键参与者网络和逐步过渡控制策略.
科学领域:
背景情况:
研究的目的:
主要方法:
主要成果:
06:45Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
Published on: October 28, 2022
11:54Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
Published on: May 8, 2021
结论: