Research Initiation Award: Robust Identification in H-infinity

H ∞理论已被广泛接受为鲁棒的 控制系统的设计，以应付不准确的 数学模型的描述。 然而，在这方面， 存在非常少的识别技术， 与当前鲁棒控制设计兼容 方法论。 系统辨识问题 因此，用公式表示H无穷大，以获得确定的 上界显式系统模型 基于H ∞范数辨识误差 实验信息（噪声数据）。 这项建议 旨在开发面向控制的识别 在H-无穷大框架下的线性 时不变系统 拟议的研究将 重点关注以下问题： 1. 建立符合实际的噪声模型 H-infinity框架; 2. 研究线性算法在 系统识别; 3. 发展稳健收敛 不同的识别算法 先验上界噪声模型 在H ∞时的识别错误 规范; 4. 鲁棒地优化性能 收敛识别算法; 5. 基于H ∞的系统辨识研究 实验噪声时间响应数据。 这项提案的最终目标是更新 识别技术，以便它们兼容 现代的鲁棒控制方法。

H-infinity theory has been widely accepted for robust control system design to cope with the inaccurate description of the mathematical models. However, there exist very few identification techniques which are compatible with current robust control design methodologies. The problem of system identification in H-infinity is thus formulated to obtain an identified system model with explicit upper bound on identification error in H-infinity norm based on experimental information (noisy data). This proposal aims to develop control oriented identification techniques in H-infinity framework for linear time-invariant systems. The proposed research will focus on following issues: 1. Establish practical noise models which fit the H-infinity framework; 2. Investigate the role of linear algorithms in system identification; 3. Develop robustly convergent identification algorithms for different noise models with priori upper bounds for identification error in H-infinity norm; 4. Optimize the performance of robustly convergent identification algorithms; 5. Study system identification in H-infinity based on experimental noisy time response data. The ultimate goal of this proposal is to update identification techniques so that they are compatible with modern robust control methodologies.