This book investigates the theoretical and practical aspects of optimal control for distributed systems, focusing on conjugation conditions within a nonconvex optimization framework. It addresses the challenges of designing control strategies for systems described by partial differential equations or other distributed phenomena, where the control objectives are often complex and the system dynamics are nonlinear. The work presents novel mathematical methods and algorithms to tackle these problems, aiming to provide robust and efficient solutions for engineers and researchers in fields such as automation, robotics, and process control.

This monograph is recognized as a specialized contribution to the field of optimal control, likely appealing to advanced students and researchers in applied mathematics and control engineering. Its focus on nonconvex optimization and conjugation conditions suggests a rigorous theoretical treatment rather than a broad introductory overview. The work is expected to be of value for those grappling with complex, real-world control problems where traditional linear methods are insufficient.