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This paper presents a new method for synthesizing stochastic control Lyapunov functions for a class of nonlinear stochastic control systems. The technique relies on a transformation of the classical nonlinear Hamilton-Jacobi-Bellman partial…

Optimization and Control · Mathematics 2017-09-07 Yoke Peng Leong , Matanya B. Horowitz , Joel W. Burdick

We prove optimality principles for semicontinuous bounded viscosity solutions of Hamilton-Jacobi-Bellman equations. In particular we provide a representation formula for viscosity supersolutions as value functions of suitable obstacle…

Optimization and Control · Mathematics 2007-05-23 Annalisa Cesaroni

This paper presents an inverse optimality method to solve the Hamilton-Jacobi-Bellman equation for a class of nonlinear problems for which the cost is quadratic and the dynamics are affine in the input. The method is inverse optimal because…

Optimization and Control · Mathematics 2011-10-11 Luis Rodrigues , Didier Henrion , Mehdi Abedinpour Fallah

Recent results in the study of the Hamilton Jacobi Bellman (HJB) equation have led to the discovery of a formulation of the value function as a linear Partial Differential Equation (PDE) for stochastic nonlinear systems with a mild…

Optimization and Control · Mathematics 2014-02-13 Matanya B. Horowitz , Joel W. Burdick

This paper considers linear-quadratic control of a non-linear dynamical system subject to arbitrary cost. I show that for this class of stochastic control problems the non-linear Hamilton-Jacobi-Bellman equation can be transformed into a…

General Physics · Physics 2009-11-11 H. J. Kappen

The paper deals with the control and regulation by integral controllers forthe nonlinear systems governed by scalar quasi-linear hyperbolic partial differentialequations. Both the control input and the measured output are located on the…

Analysis of PDEs · Mathematics 2019-04-30 Vincent Andrieu , Ngoc-Tu Trinh , Cheng-Zhong Xu

This paper proposes a line integral Lyapunov function approach to stability analysis and stabilization for It\^o stochastic T-S models. Unlike the deterministic case, stability analysis of this model needs the information of Hessian matrix…

Systems and Control · Electrical Eng. & Systems 2020-04-02 Shaosheng Zhou , Yingying Han , Baoyong Zhang

While ensuring stability for linear systems is well understood, it remains a major challenge for nonlinear systems. A general approach in such cases is to compute a combination of a Lyapunov function and an associated control policy.…

Machine Learning · Computer Science 2023-12-27 Junlin Wu , Andrew Clark , Yiannis Kantaros , Yevgeniy Vorobeychik

We introduce a method for controlling systems with nonlinear dynamics and full actuation by approximating the dynamics with polynomials and applying a system level synthesis controller. We show how to optimize over this class of controllers…

Optimization and Control · Mathematics 2023-06-09 Lauren Conger , Syndey Vernon , Eric Mazumdar

This paper presents a method to approximately solve stochastic optimal control problems in which the cost function and the system dynamics are polynomial. For stochastic systems with polynomial dynamics, the moments of the state can be…

Optimization and Control · Mathematics 2017-02-24 Andrew Lamperski , Khem Raj Ghusinga , Abhyudai Singh

Control Lyapunov function is a central tool in stabilization. It generalizes an abstract energy function -- a Lyapunov function -- to the case of controlled systems. It is a known fact that most control Lyapunov functions are non-smooth --…

Optimization and Control · Mathematics 2022-11-08 Pavel Osinenko , Grigory Yaremenko , Georgiy Malaniya

This paper studies the problem of constructing control Lyapunov functions (CLFs) and feedback stabilization strategies for deterministic nonlinear control systems described by ordinary differential equations. Many numerical methods for…

Optimization and Control · Mathematics 2024-09-23 Ivan Yegorov , Peter M. Dower , Lars Grüne

We consider the problem of designing a stabilizing and optimal static controller with a pre-specified sparsity pattern. Since this problem is NP-hard in general, it is necessary to resort to approximation approaches. In this paper, we…

Systems and Control · Computer Science 2019-09-26 Luca Furieri , Yang Zheng , Antonis Papachristodoulou , Maryam Kamgarpour

This paper presents a new methodology to craft navigation functions for nonlinear systems with stochastic uncertainty. The method relies on the transformation of the Hamilton-Jacobi-Bellman (HJB) equation into a linear partial differential…

Robotics · Computer Science 2014-09-23 Matanya B. Horowitz , Joel W. Burdick

We introduce High-Relative Degree Stochastic Control Lyapunov functions and Barrier Functions as a means to ensure asymptotic stability of the system and incorporate state dependent high relative degree safety constraints on a non-linear…

Systems and Control · Electrical Eng. & Systems 2020-04-09 Meenakshi Sarkar , Debasish Ghose , Evangelos A. Theodorou

Hyperexponential stability is investigated for dynamical systems with the use of both, explicit and implicit, Lyapunov function methods. A nonlinear hyperexponential control is designed for stabilizing linear systems. The tuning procedure…

Systems and Control · Electrical Eng. & Systems 2022-07-19 Konstantin Zimenko , Denis Efimov , Andrey Polyakov

The Lyapunov inequality is an indispensable tool for stability analysis in linear control theory. It provides a necessary and sufficient condition for the stability of an autonomous linear-time invariant system in terms of the existence of…

Optimization and Control · Mathematics 2025-12-24 Avinash Kumar

We give a new perspective on the existence of viscosity solutions for a stationary and a time-dependent first-order Hamilton-Jacobi equation. Following recent comparison principles, we work in a framework in which we consider a subsolution…

Analysis of PDEs · Mathematics 2025-11-25 Serena Della Corte , Richard C. Kraaij

A general bilinear optimal control problem subject to an infinite-dimensional state equation is considered. Polynomial approximations of the associated value function are derived around the steady state by repeated formal differentiation of…

Optimization and Control · Mathematics 2017-06-19 Tobias Breiten , Karl Kunisch , Laurent Pfeiffer

This paper presents a two-stage framework for constrained near-optimal feedback control of input-affine nonlinear systems. An approximate value function for the unconstrained control problem is computed offline by solving the…

Systems and Control · Electrical Eng. & Systems 2026-03-18 Milad Alipour Shahraki , Laurent Lessard
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