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This book presents a methodology for fault diagnosis detection, isolation, and identification for§dynamic systems whose models are faced with parametric §uncertainties. This class of problems is often§encountered in practice, and has not been§exclusively dealt with in the past. The book begins§with a§review of existing literature on model-based, in§particular, observer-based fault§diagnosis for linear and nonlinear dynamic systems.§It then§focuses on a novel observer-based fault diagnosis§technique for linear time-invariant systems with§parametric uncertainties. The underlying§observer-design utilizes recent§results in the area of robust control of dynamic§systems with parametric uncertainties, and§is grounded in Kharitonov s theorem of stability of§Interval polynomials. This paradigm of fault§diagnosis is then extended to nonlinear dynamic§systems with parametric uncertainties. The remaining§part of the book extends the proposed model-based§fault diagnosis methodology to empirical state-space§models derived from input-output data using subspace§model identification.