Each chapter functions as a stand-alone guide for understanding and applying theory!

Focusing on the special class of linear control systems known as singularly perturbed control systems, this detailed reference/text summarizes current knowledge of the Hamiltonian approach and develops parallel algorithms in slow and fast time scales for numerous dynamic control systems.

Presents a unified study of the recursive approach based on the Hamiltonian approach for exact pure-slow and pure-fast decoupling of optimal control problems!

Constructing a unique method applicable to a number of challenging real-world control systems, Optimal Control of Singularly Perturbed Linear Systems and Applications

• reveals how to achieve high accuracy using slow-fast time scales for deterministic and stochastic, continuous- and discrete-time, linear-quadratic optimal control, and filtering problems
• illustrates high gain feedback and cheap control engineering problems, sampled data systems, and H_oo optimization with helpful case studies
• demonstrates theoretical results from examples in the aerospace, chemical, electrical, and automotive industries
• simplifies hardware implementation of optimal controllers and filters
• considers the eigenvector approach for the algebraic Riccati equations
• identifies unsolved discrete-time domain and finite horizon optimization problems for future research
• and more!

Consolidating results from the authors’ extensive research experiences, Optimal Control of Singularly Perturbed Linear Systems and Applications satisfies the reference needs of electrical and electronics engineers, applied mathematicians, physicists, and computer scientists; and serves as a useful textbook for graduate students in these disciplines.