Observability and Identifiability of Nonlinear Systems Driven by Unknown Inputs: Algebraic Solution and Practical Implementation in Matlab(r)

This book provides the first complete algebraic framework for solving two long-standing open problems in systems theory: observability in the presence of unknown inputs and identifiability of time-varying parameters. The framework provides necessary and sufficient conditions, together with constructive algorithms, for solving both problems in general nonlinear systems. The same algebraic framework also introduces the unknown input identifier (UID)-induced normal form, revealing the structural decomposition underlying nonlinear systems with unknown inputs and providing the foundation for unknown-input decoupling and observer design.

The theoretical developments are complemented by a chapter on the TUIO Toolbox for MATLAB(R), which enables symbolic observability and identifiability analysis and illustrates the proposed methods with representative examples from biology and engineering. Combining rigorous theory with practical tools, this book provides a valuable resource for researchers and advanced graduate students working on nonlinear systems, control, robotics, computer vision, systems biology, and related fields.