Research Initiation Award: Adaptive Quantification of Model Uncertainties

鲁棒控制中的一个关键因素 自适应控制是一种合理的 不确定性边界 不足 不确定性约束描述将 导致分析过度 保守或危险 乐观 尽管如此，广泛 这是一个令人赞赏的事实， 不确定性的量化 很少受到关注。 的 研究旨在开发一种新的 估算方法 真正的植物， 频率上界 不确定性 一个起点是 自适应量化 理性不确定性 近似结合 识别、插值和 很好的近似。 初步 结果表明，所提出的方法 提供了现实的界限， 不确定性 这鼓励我们 相信有相当多的 进一步探索的潜力。 预期的开展战略 本研究概述。 的 潜在的好处和 预期结果的影响 被认为是广泛的， 包括对 认识和对待 不确定性的影响， 鲁棒控制与 自适应控制，故障诊断新方法 检测等等。

A key element needed in robust control and adaptive control is a reasonable uncertainty bound. An inadequate uncertainty bound description will cause analysis to be either overly conservative or dangerously optimistic. Despite this widely appreciated fact, the problem of the quantification of uncertainty has received scant attention. The research intends to develop a new methodology for obtaining an estimate of the true plant as well as a frequency upper bound on the uncertainty. A starting point is the adaptive quantification of uncertainties by rational approximation which combines identification, interpolation and approximation nicely. Preliminary results show that the methods proposed provide realistic bounds for the uncertainty. This encourages us to believe that there is considerable potential for further exploration. The expected strategies for conducting this research are outlined. The potential benefits and the implications of the expected results are believed to be wide-ranging and include new insights into the understanding and treatment of the effects of the uncertainty, integration of robust control and adaptive control, new method for fault detection and so on.