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Deep learning has had a far reaching impact in robotics. Specifically, deep reinforcement learning algorithms have been highly effective in synthesizing neural-network controllers for a wide range of tasks. However, despite this empirical…

Robotics · Computer Science 2021-09-30 Hongkai Dai , Benoit Landry , Lujie Yang , Marco Pavone , Russ Tedrake

Control theory can provide useful insights into the properties of controlled, dynamic systems. One important property of nonlinear systems is the region of attraction (ROA), a safe subset of the state space in which a given controller…

Systems and Control · Computer Science 2017-08-17 Felix Berkenkamp , Riccardo Moriconi , Angela P. Schoellig , Andreas Krause

A robust controller is developed for uncertain, second-order nonlinear systems subject to simultaneous unknown, time-varying state delays and known, time-varying input delays in addition to additive, sufficiently smooth disturbances. An…

Systems and Control · Computer Science 2017-07-25 Rushikesh Kamalapurkar , Nicholas Fischer , Serhat Obuz , Warren E. Dixon

This article presents novel methods for synthesizing distributionally robust stabilizing neural controllers and certificates for control systems under model uncertainty. A key challenge in designing controllers with stability guarantees for…

Systems and Control · Electrical Eng. & Systems 2024-08-06 Kehan Long , Jorge Cortes , Nikolay Atanasov

This paper presents a nonlinear model predictive control strategy for stochastic systems with general (state and input dependent) disturbances subject to chance constraints. Our approach uses an online computed stochastic tube to ensure…

Systems and Control · Electrical Eng. & Systems 2022-07-19 Henning Schlüter , Frank Allgöwer

This paper proposes a new stability analysis for the Reaction Torque Observer (RTOb) based robust force control systems in the discrete-time domain. The robust force controller is implemented by employing a Disturbance Observer (DOb) to…

Systems and Control · Electrical Eng. & Systems 2023-02-07 Emre Sariyildiz

An interlaced method to learn and control nonlinear system dynamics from a set of demonstrations is proposed, under a constrained optimization framework for the unsupervised learning process. The nonlinear system is modelled as a mixture of…

Systems and Control · Electrical Eng. & Systems 2024-10-17 Yeyson A. Becerra-Mora , José Ángel Acosta

This paper presents a robust control synthesis and analysis framework for nonlinear systems with uncertain initial conditions. First, a deep learning-based lifting approach is proposed to approximate nonlinear dynamical systems with linear…

Systems and Control · Electrical Eng. & Systems 2026-01-06 Sourav Sinha , Mazen Farhood

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

The robust tracking and model following problem of linear discrete-time systems is investigated in this paper. An approach to design robust tracking controllers is proposed. The system is controlled to track dynamic inputs generated from a…

Systems and Control · Computer Science 2016-07-12 Omar Zakary , Mostafa Rachik

Stability analysis tools are essential to understanding and controlling any engineering system. Recently sum-of-squares (SOS) based methods have been used to compute Lyapunov based estimates for the region-of-attraction (ROA) of polynomial…

Dynamical Systems · Mathematics 2015-01-23 Soumya Kundu , Marian Anghel

In this paper, we present Lyapunov-based {\color{black}time varying} controllers for {\color{black}fast} stabilization of a perturbed chain of integrators with bounded uncertainties. We refer to such controllers as {\color{black}time…

Optimization and Control · Mathematics 2020-02-26 Salah Laghrouche , Mohamed Harmouche , Yacine Chitour , Hussein Obeid , Leonid Fridman

This work provides a framework for data-driven control of discrete time systems with unknown input-output dynamics and outputs controllable by the inputs. This framework leads to stable and robust real-time control of the system such that a…

Systems and Control · Electrical Eng. & Systems 2021-04-02 Amit K. Sanyal

In this paper, we focus on the problem about direct way to design a stable controller for nonlinear system. A framework of learning controller with Lyapunov-based constraint is proposed, which is intended to transform designing and analyis…

Systems and Control · Computer Science 2019-03-11 Me Le , Chi Yanxun , Li Zhiwei , Xu Dongfu , Zhang Yulong

To provide robustness of distributed model predictive control (DMPC), this work proposes a robust DMPC formulation for discrete-time linear systems subject to unknown-but-bounded disturbances. Taking advantage of the structure of certain…

Systems and Control · Electrical Eng. & Systems 2021-03-10 Ye Wang , Chris Manzie

This paper addresses the problem of risk-aware fixed-time stabilization of a class of uncertain, output-feedback nonlinear systems modeled via stochastic differential equations. First, novel classes of certificate functions, namely…

Optimization and Control · Mathematics 2024-04-01 Mitchell Black , Georgios Fainekos , Bardh Hoxha , Dimitra Panagou

A controller synthesis method for state- and input-constrained nonlinear systems is presented that seeks continuous piecewise affine (CPA) Lyapunov-like functions and controllers simultaneously. Non-convex optimization problems are…

Systems and Control · Electrical Eng. & Systems 2022-03-08 Reza Lavaei , Leila Bridgeman

We derive a saturated feedback control, which locally stabilizes a linear reaction-diffusion equation. In contrast to most other works on this topic, we do not assume the Lyapunov stability of the uncontrolled system and consider general…

Optimization and Control · Mathematics 2020-07-07 Andrii Mironchenko , Christophe Prieur , Fabian Wirth

This paper presents an optimal dynamic control framework for bounded Jacobian nonlinear discrete-time (DT) systems with nonlinear observations affected by both state and process noise. Rather than directly stabilizing the uncertain system,…

Systems and Control · Electrical Eng. & Systems 2025-05-01 Mohammad Khajenejad

The stability analysis of a class of discontinuous discrete-time systems is studied in this paper. The system under study is modeled as a feedback interconnection of a linear system and a set-valued nonlinearity. An equivalent…

Systems and Control · Electrical Eng. & Systems 2022-08-12 Francesco Ferrante , Giorgio Valmorbida