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Geometry of adaptive control: optimization and geodesies

机译:自适应控制的几何:优化和大地测量

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Two incompatible topologies appear in the study of adaptive systems: the graph topology in control design, and the coefficient topology in system identification. Their incompatibility is manifest in the stabilization problem of adaptive control. We argue that this problem can be approached by changing the geometry of the sets of control systems under consideration: estimating n_p parameters in an n_p-dimensional manifold whose points all correspond to stabilizable systems. One way to construct the manifold is using the properties of the algebraic Riccati equation. Parameter estimation can be approached as an optimal control problem akin to the deterministic Kalman filter, leading to algorithms that can be used in conjunction with standard observers and controllers to construct stable adaptive systems.
机译:自适应系统的研究中出现了两种不兼容的拓扑:控制设计中的图形拓扑和系统识别中的系数拓扑。它们的不兼容表现在自适应控制的稳定问题上。我们认为,可以通过更改所考虑的控制系统集合的几何来解决此问题:估计n_p维流形中的n_p个参数,这些点都对应于可稳定系统。构造流形的一种方法是使用代数Riccati方程的性质。可以将参数估计作为类似于确定性卡尔曼滤波器的最佳控制问题,从而得出可以与标准观察者和控制器结合使用以构建稳定的自适应系统的算法。

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