This book provides a comprehensive treatment of the development and present state of the theory of sensitivity of dynamic systems. It is intended as a textbook and reference for researchers and scientists in electrical engineering, control and information theory as well as for mathematicians. The extensive and structured bibliography provides an overview of the literature in the field and points out directions for further research.
Linear-Quadratic Controls in Risk-Averse Decision Making cuts across control engineering (control feedback and decision optimization) and statistics (post-design performance analysis) with a common theme: reliability increase seen from the responsive angle of incorporating and engineering multi-level performance robustness beyond the long-run average performance into control feedback design and decision making and complex dynamic systems from the start. This monograph provides a complete description of statistical optimal control (also known as cost-cumulant control) theory. In control problems and topics, emphasis is primarily placed on major developments attained and explicit connections between mathematical statistics of performance appraisals and decision and control optimization. Chapter summaries shed light on the relevance of developed results, which makes this monograph suitable for graduate-level lectures in applied mathematics and electrical engineering with systems-theoretic concentration, elective study or a reference for interested readers, researchers, and graduate students who are interested in theoretical constructs and design principles for stochastic controlled systems.
Sensitivity Methods in Control Theory is a collection of manuscripts presented as the Third International Symposium of Sensitivity Analysis, held at Dubrovnik, Yugoslavia on August 31-September 5, 1964, sponsored by The Theory Committee of International Federation of Automatic Control. Sensitivity theory or sensitivity analysis concerns the solution of problems associated with parameter variations within the general scope of control theory. This book is organized into five parts encompassing 30 chapters. Part I presents some basic approaches of sensitivity analysis, such the Lyapunov's theory of stability, invariant imbedding, nonlinear sampled data, and linear time-varying systems. This part also looks into the preliminary steps towards the development of game theory and some general applications of sensitivity analysis. Part II treats the problem of accuracy, reliability, self-adjustment, and optimization of sensitivity of automatic control systems, while Part III deals with the functional derivative technique of sensitivity analysis and its applications for designing self-adjusting control systems. Part IV describes the task of synthesizing control systems for linear plants with variable parameters satisfying specified performance criteria. Part V considers the association between sensitivity and optimality in various control systems. This book will prove useful to design and other specialized fields in engineering.
