Search Results for author: Jean-Jacques E. Slotine

Found 12 papers, 3 papers with code

Random features for adaptive nonlinear control and prediction

no code implementations7 Jun 2021 Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

A key assumption in the theory of adaptive control for nonlinear systems is that the uncertainty of the system can be expressed in the linear span of a set of known basis functions.

Adaptive Variants of Optimal Feedback Policies

no code implementations6 Apr 2021 Brett T. Lopez, Jean-Jacques E. Slotine

We combine adaptive control directly with optimal or near-optimal value functions to enhance stability and closed-loop performance in systems with parametric uncertainties.

Universal Adaptive Control of Nonlinear Systems

no code implementations31 Dec 2020 Brett T. Lopez, Jean-Jacques E. Slotine

This work develops a new direct adaptive control framework that extends the certainty equivalence principle to general nonlinear systems with unmatched model uncertainties.

Motion Planning Transfer Learning

Regret Bounds for Adaptive Nonlinear Control

no code implementations26 Nov 2020 Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

We study the problem of adaptively controlling a known discrete-time nonlinear system subject to unmodeled disturbances.

Neural Stochastic Contraction Metrics for Learning-based Control and Estimation

1 code implementation6 Nov 2020 Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

We present Neural Stochastic Contraction Metrics (NSCM), a new design framework for provably-stable robust control and estimation for a class of stochastic nonlinear systems.

Learning Stability Certificates from Data

no code implementations13 Aug 2020 Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani

Many existing tools in nonlinear control theory for establishing stability or safety of a dynamical system can be distilled to the construction of a certificate function that guarantees a desired property.

The Reflectron: Exploiting geometry for learning generalized linear models

no code implementations15 Jun 2020 Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

By analogy to standard mirror descent, we show that the methods can be tailored to the $\textit{problem geometry}$ through choice of a potential function that defines the $\textit{optimization geometry}$.

Implicit regularization and momentum algorithms in nonlinear adaptive control and prediction

no code implementations31 Dec 2019 Nicholas M. Boffi, Jean-Jacques E. Slotine

We show that the Euler Lagrange equations for the Bregman Lagrangian lead to natural gradient and mirror descent-like adaptation laws with momentum, and we recover their first-order analogues in the infinite friction limit.

Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization

1 code implementation29 Jul 2019 Sumeet Singh, Spencer M. Richards, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone

We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics.

Continuous Control

A continuous-time analysis of distributed stochastic gradient

no code implementations28 Dec 2018 Nicholas M. Boffi, Jean-Jacques E. Slotine

We analyze the effect of synchronization on distributed stochastic gradient algorithms.

Distributed Optimization

Observability in Inertial Parameter Identification

2 code implementations10 Nov 2017 Patrick M. Wensing, Günter Niemeyer, Jean-Jacques E. Slotine

We present an algorithm to characterize the space of identifiable inertial parameters in system identification of an articulated robot.


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