离散时间输入-关联系统的智能-批判-基于跟踪控制和近似错误分析与应用程序验证
IEEE transactions on cybernetics
|October 5, 2023
概括
本研究解决了离散时间系统最佳控制中的近似误差. 一种新的方法可以确保系统稳定,尽管存在这些错误,通过示例验证.
科学领域:
- 控制理论 控制理论
- 机器学习 机器学习
- 系统工程 系统工程
背景情况:
- 最佳控制问题正在与神经网络等函数近似器一起发展.
- 这些系统中的近似误差可能会损害受控系统的稳定性.
- 离散时间系统容易受到这些稳定性挑战的影响.
研究的目的:
- 为了研究离散时间系统与近似误差的最佳跟踪控制.
- 开发一种方法,在存在近似误差的情况下保证系统稳定性.
- 引入一种用于代最佳控制问题解决的新方法.
主要方法:
- 在智能批评框架内引入一种新的价值函数.
- 使用隐式方法来证明代值函数与近似误差的边界性.
- 应用明确的方法来证明系统稳定性,尽管近似误差.
- 为代的最佳跟踪控制设计一个不断变化的政策.
主要成果:
- 在存在近似误差的情况下证明了代值函数的边界性.
- 证明了离散时间系统与近似误差的稳定性.
- 制定了不断发展的政策,以代方式解决最佳跟踪控制问题.
- 通过数值和实践示例验证了方法的有效性.
结论:
- 拟议的方法确保了系统稳定性,以在离散时间系统中实现最佳的跟踪控制,即使有近似误差.
- 智能批评框架,增强了新的价值函数,有效地处理近似错误.
- 开发的不断发展的政策为复杂的最佳控制挑战提供了强大的解决方案.
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