Design of Hybrid Adaptive and Learning Control Systems under Complex Environment via Nonlinear H-Infinity Control Scheme

本课题通过扩展控制理论中的自适应控制、非线性控制和鲁棒控制等方法，应用神经网络、模糊控制、遗传算法和增强学习等智能控制工具，构建了在复杂环境下具有较高适应能力的混合自适应和学习控制系统的设计方案。通过这样做，研究创造了信息科学和工程的新领域，并在系统和控制科学中发展了一致的理论方法。

This research project constructed design schemes of hybrid adaptive and learning control systems which contain high adaptation abilities under complicated environments, by extending several methodologies in control theory such as adaptive control, nonlinear control and robust control, and by applying several tools in intelligent control such as neural networks, fuzzy control, genetic algorithms and enhance learning. By doing so, the research created new fields in information science and engineering, and developed consistent and theoretical methodologies in system and control science.