Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates

Iterative optimization algorithms depend on access to information about the objective function. In a differentiable programming framework, this information, such as gradients, can be automatically derived from the computational graph. We explore how nonlinear control algorithms, often employing line...

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Detalles Bibliográficos

Autores principales:	Roulet, Vincent, Srinivasa, Siddhartha, Fazel, Maryam, Harchaoui, Zaid
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Université de Montpellier 2024-11-01
Colección:	Open Journal of Mathematical Optimization
Materias:	Nonlinear Discrete Time Control Differentiable Programming Newton Gauss–Newton Dynamic Differentiable Programming
Acceso en línea:	https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.32/
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