Linear Parameter-Varying System Identification: New Developments and Trends (Advanced Series in Electrical and Computer Engineering)

Hardcover, xv + 385 pages, NOT ex-library. Book looks unread, clean and bright throughout with unmarked text, free of inscriptions and stamps, firmly bound. Issued without a dust jacket. -- This book provides an overview of the Linear Parameter-Varying (LPV) framework, a sophisticated approach to modelling and controlling systems that change their behaviour based on external variables. It acts as a bridge between simple linear systems and complex non-linear ones, offering tools to identify these systems from experimental data. The LPV approach assumes that a system's dynamics are linear, but its parameters (such as gain or time constants) vary as a function of an independent, measurable signal called the scheduling variable. This allows engineers to model non-linear systems - such as aircraft with changing altitudes or chemical reactors with varying temperatures - using extended linear techniques. The volume highlights several modern advancements in the field: - Subspace Identification Methods: A significant portion of the text focuses on subspace algorithms, which are particularly effective for identifying multi-variable (MIMO) LPV systems directly from data without needing complex initial guesses; - Input-Output vs. State-Space Models: The authors discuss the trade-offs between identifying input-output representations (simpler to calculate) versus state-space models (more useful for advanced control design); - Frequency Domain Techniques: It explores how frequency response data can be used to identify LPV models, a traditional method in aerospace engineering; - Basis Function Selection: The book addresses the critical challenge of choosing the right mathematical "basis functions" to describe how parameters vary, ensuring the model remains accurate across the entire operating range. Practical Applications: The methods described are essential for industries dealing with "varying-regime" operations: - Aerospace: Modelling flight dynamics across different Mach numbers and altitudes; - Automotive: Designing active suspension or engine control systems that adapt to vehicle speed; - Process Control: Managing industrial plants where the chemical properties of a product change during the manufacturing cycle. The book is a collaborative effort by international experts, including Paulo Lopes dos Santos and Daniel E. Rivera, combining academic rigour with insights into practical implementation. It serves as a high-level reference for postgraduate students and research engineers in automatic control and signal processing.…