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Advances in Control Systems: Theory and Applications, Volume 6 provides information pertinent to the significant progress in the field of control and systems theory and applications. This book presents the higher level of automata, which represent the embodiment of the application of artificial intelligence techniques to control system design and may be described as self-organizing systems. Organized into four chapters, this volume begins with an overview of the existing technology in learning control system. This text then demonstrates how to apply artificial intelligence techniques to the designs of off-line and on-line learning control systems. Other chapters consider the decomposition methods and the associated multilevel optimization techniques applicable to control system optimization problems. This book discusses as well the complex optimal system control problems applied to the trajectory optimization problem. The final chapter deals with systems described by partial differential equations. This book is a valuable resource for control system engineers. Content: Contributors to this VolumePage ii Front MatterPage iii Copyright pagePage iv ContributorsPage v PrefacePages vii-viiiC.T. LEONDES Contents of Previous VolumesPages xi-xiii The Application of Techniques of Artificial Intelligence to Control System DesignPages 1-94JERRY M. MENDEL, JAMES J. ZAPALAC Controllability and Observability of Linear, Stochastic, Time Discrete Control Sytems*Pages 95-158H.W. SORENSON Multilevel Optimization Techniques with Application to Trajectory DecompositionPages 159-220EDWARD JAMES BAUMAN Optimal Control Theory Applied to Systems Described by Partial Differential EquationsPages 221-316WILLIAM L. BROGAN Author IndexPages 317-319 Subject IndexPages 320-321