Linear-Quadratic Controls in Risk-Averse Decision Making
Subtitle: Performance-Measure Statistics and Control Decision Optimization
By: by Khanh D. Pham
Contributors: SpringerLink (Online service)
Series: SpringerBriefs in Optimization
Publisher: Springer New York; Imprint: Springer
Published: 2013
Place of publication: New York, NY
Language: eng
Format: [electronic resource] :
Number of pages: 150
ISBN-13: 9781461450795
Subjects: Dynamical Systems and Ergodic Theory; Calculus of Variations and Optimal Control; Optimization; Statistical Theory and Methods; Mathematical statistics; Computer science; Differentiable dynamical systems; Mathematics; Mathematical optimization; Computational Science and Engineering
Description: ​​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.​