Providing readers with a detailed examination of resilient controls in risk-averse decision, this monograph is aimed toward researchers and graduate students in applied mathematics and electrical engineering with a systems-theoretic concentration. This work contains a timely and responsive evaluation of reforms on the use of asymmetry or skewness pertaining to the restrictive family of quadratic costs that have been appeared in various scholarly forums. Additionally, the book includes a discussion of the current and ongoing efforts in the usage of risk, dynamic game decision optimization and disturbance mitigation techniques with output feedback measurements tailored toward the worst-case scenarios. This work encompasses some of the curren...
This book provides a comprehensive presentation of classical and advanced topics in estimation and c...
This thesis dives into the theory of discrete time stochastic optimal control through exploring dyna...
This thesis develops various methods for the robust and stochastic model-based control of uncertain ...
When faced with uncertainty regarding potential failure contingencies, prioritizing system resilienc...
This paper discusses the con trot of nonlinear stochastic systems and, in particular, linear systems...
The objective of this paper is to correct and improve the results obtained by Van der Ploeg (1984a, ...
The chapters in this volume, and the volume itself, celebrate the life and research of Roberto Tempo...
Resilience is a rehashed concept in natural hazard management — resilience of cities to earthquakes,...
We consider the problem of controlling an unknown stochastic linear dynamical system subject to an i...
We consider the problem of stochastic control under power constraints. Problems such as linear quadr...
Uncertainty presents significant challenges in the reasoning about and controlling of complex dynami...
In this paper, we attempt to invent a new way to understand risk, measure it, and weigh its conseque...
This paper clarifies the relationship between risksensitive and robust control. This topic has recei...
Abstmet-Three parallel gaps in robust feedback control theory are examined: sufficiency versus neces...
In this paper, we show that for arbitrary stochastic linear dynamical systems, the problem of optimi...
This book provides a comprehensive presentation of classical and advanced topics in estimation and c...
This thesis dives into the theory of discrete time stochastic optimal control through exploring dyna...
This thesis develops various methods for the robust and stochastic model-based control of uncertain ...
When faced with uncertainty regarding potential failure contingencies, prioritizing system resilienc...
This paper discusses the con trot of nonlinear stochastic systems and, in particular, linear systems...
The objective of this paper is to correct and improve the results obtained by Van der Ploeg (1984a, ...
The chapters in this volume, and the volume itself, celebrate the life and research of Roberto Tempo...
Resilience is a rehashed concept in natural hazard management — resilience of cities to earthquakes,...
We consider the problem of controlling an unknown stochastic linear dynamical system subject to an i...
We consider the problem of stochastic control under power constraints. Problems such as linear quadr...
Uncertainty presents significant challenges in the reasoning about and controlling of complex dynami...
In this paper, we attempt to invent a new way to understand risk, measure it, and weigh its conseque...
This paper clarifies the relationship between risksensitive and robust control. This topic has recei...
Abstmet-Three parallel gaps in robust feedback control theory are examined: sufficiency versus neces...
In this paper, we show that for arbitrary stochastic linear dynamical systems, the problem of optimi...
This book provides a comprehensive presentation of classical and advanced topics in estimation and c...
This thesis dives into the theory of discrete time stochastic optimal control through exploring dyna...
This thesis develops various methods for the robust and stochastic model-based control of uncertain ...