This work studies the design of safe control policies for large-scale non-linear systems operating in uncertain environments. In such a case, the robust control framework is a principled approach to safety that aims to maximize the worst-case performance of a system. However, the resulting optimization problem is generally intractable for non-linear systems with continuous states. To overcome this issue, we introduce two tractable methods that are based either on sampling or on a conservative approximation of the robust objective. The proposed approaches are applied to the problem of autonomous driving
Existing methods for nonlinear robust control often use scenario-based approaches to formulate the c...
This thesis is about robust optimization, a class of mathematical optimization problems which arise ...
In this paper, we present a novel Reduced Robustified NMPC (R$^2$NMPC) algorithm that has the same c...
We consider the linear quadratic regulation problem when the plant is an unknown linear dynamical sy...
The grant DEFG02-97ER13939 from the Department of Energy has supported our research program on robus...
This thesis develops various methods for the robust and stochastic model-based control of uncertain ...
Robust control is a core approach for controlling systems with performance guarantees that are robus...
Abstract In this paper, we propose a new methodology for handling opti-mization problems with uncert...
International audienceWe describe several problems of " robust control " that have a solution using ...
In this chapter, adaptive gain robust control strategies for uncertain dynamical systems are present...
Performance analysis of a large class of nonlinear systems is proven to be equivalent to performance...
Control design for nonlinear dynamical systems is an essential field of study in a world growing eve...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
Safety is an important aim in designing safe-critical systems. To design such systems, many policy i...
This study discusses a robust controller synthesis methodology for linear, time invariant systems, u...
Existing methods for nonlinear robust control often use scenario-based approaches to formulate the c...
This thesis is about robust optimization, a class of mathematical optimization problems which arise ...
In this paper, we present a novel Reduced Robustified NMPC (R$^2$NMPC) algorithm that has the same c...
We consider the linear quadratic regulation problem when the plant is an unknown linear dynamical sy...
The grant DEFG02-97ER13939 from the Department of Energy has supported our research program on robus...
This thesis develops various methods for the robust and stochastic model-based control of uncertain ...
Robust control is a core approach for controlling systems with performance guarantees that are robus...
Abstract In this paper, we propose a new methodology for handling opti-mization problems with uncert...
International audienceWe describe several problems of " robust control " that have a solution using ...
In this chapter, adaptive gain robust control strategies for uncertain dynamical systems are present...
Performance analysis of a large class of nonlinear systems is proven to be equivalent to performance...
Control design for nonlinear dynamical systems is an essential field of study in a world growing eve...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
Safety is an important aim in designing safe-critical systems. To design such systems, many policy i...
This study discusses a robust controller synthesis methodology for linear, time invariant systems, u...
Existing methods for nonlinear robust control often use scenario-based approaches to formulate the c...
This thesis is about robust optimization, a class of mathematical optimization problems which arise ...
In this paper, we present a novel Reduced Robustified NMPC (R$^2$NMPC) algorithm that has the same c...