适应性动态编程用于具有非对称输入约束的非线性系统的强有力的事件驱动的跟踪控制.
IEEE transactions on cybernetics
|July 19, 2024
概括
本研究介绍了对具有输入约束的非线性系统的强大的动态事件驱动跟踪控制. 它使用一种新的方法来减少计算负载并确保系统稳定性.
科学领域:
- 控制理论 控制理论
- 非线性系统是非线性系统.
- 适应式动态编程 (ADP) 是一种动态编程.
背景情况:
- 由于干扰和输入限制,非线性系统在控制方面存在挑战.
- 不对称的输入约束使传统的控制设计复杂化.
- 事件驱动控制提供了减少计算负担的潜力.
研究的目的:
- 为非线性系统开发一个强大的动态事件驱动的跟踪控制.
- 为了解决不匹配的干扰和不对称的输入约束.
- 为了减少最佳控制设计的计算负载.
主要方法:
- 构建一个新的非二次数值函数来处理不对称的约束.
- 开发动态事件驱动机制和事件驱动的汉密尔顿-雅各比-贝尔曼方程 (ED-HJBE).
- 在自适应动态编程框架内利用单个关键神经网络 (CNN),并为重量更新进行梯度下降.
主要成果:
- 不对称的约束问题转化为不受约束的最佳调节问题.
- 解决了ED-HJBE,以减少计算量产生最佳控制.
- 体重估计误差和跟踪误差的统一终极边界性是使用Lyapunov的直接方法证明的.
结论:
- 拟议的方法有效地解决了对非线性系统的强大的动态事件驱动跟踪控制.
- 该方法成功地处理了不匹配的干扰和不对称的输入约束.
- 模拟验证了对基准系统的理论发现.
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