Gray-box extremum-seeking control for real-time optimization of uncertain nonlinear systems
Gray-box extremum-seeking control for real-time optimization of uncertain nonlinear systems
复制标题
不确定非线性系统实时优化的灰盒极值搜索控制
DOI：
10.1109/acc.2015.7170844
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
M. Guay
中科院分区：
文献类型：
--
作者：
E. Moshksar;M. Guay
本文研究了具有未知代价函数和不确定动态的非线性系统的实时优化问题。动力系统的漂移项和未知目标函数的梯度被视为未知时变参数。提出了一种新的基于几乎不变流形的时变参数估计方法。设计了一种直接自适应极值搜索控制器来解决不确定优化问题。这种方法被证明是为了避免需要的时间尺度分离的实时优化算法的设计。仿真实例表明了该方法的有效性。
In this paper, a real-time optimization of nonlinear systems with unknown cost function and uncertain dynamics is considered. The drift term of the dynamical system and the gradient of the unknown objective function are treated as unknown time-varying parameters. A novel estimation scheme based on the almost invariant manifolds is proposed to estimate the unknown time-varying parameters. A direct adaptive extremum-seeking controller is designed to solve the uncertain optimization problem. This approach is shown to avoid the need for time-scale separation in design of the real-time optimization algorithm. The effectiveness of the proposed method is illustrated with a simulation example.