Control of Uncertain Sampled-Data Systems

Hybrid systems are formed when continuous-time and discrete-time systems are interconnected. The author's goal in this text is to provide a treatment of uncertainty analysis for samle-data hybrid systems in the context of robust control theory. The book has a general scope in that it offers a widely applicable and unifying viewpoint that considers a large class of structured uncertainty problems arising in control, whether the system be hybrid, discrtete-time or continuous-time. In the body of the text, operator theoretic tools and techniques are developed to address the central design issues of performance and stabilization in the presence of structured uncertainty classes. The methods are applied to exact analysis of hybrid sampled-data systems in the H-infinity or Hilbert space setting, with the focus being mu-theory and its generalizations to time-varying uncertainty structures. The mathematical machinery and framework presented provide a unified approach to studying performance and uncertainty, and is applicable to both standard and sampled-data systems.