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Adaptive Control Lyapunov Functions (aCLFs) were introduced 20 years ago, and provided a Lyapunov-based methodology for stabilizing systems with parameter uncertainty. The goal of this paper is to revisit this classic formulation in the…

Systems and Control · Electrical Eng. & Systems 2020-11-20 Andrew J. Taylor , Aaron D. Ames

In this paper, we provide a systematic approach for the design of stabilizing feedback controllers for nonlinear control systems using the Koopman operator framework. The Koopman operator approach provides a linear representation for a…

Optimization and Control · Mathematics 2018-10-02 Bowen Huang , Xu Ma , Umesh Vaidya

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 studies the cooperative global robust stabilization problem for a class of nonlinear multi-agent systems. The problem is motivated from the study of the cooperative global robust output regulation problem for the class of…

Optimization and Control · Mathematics 2015-08-20 Wei Liu , Jie Huang

This paper studies the feedback stabilization problem of the motion of a tank that contains an incompressible, Newtonian, viscous liquid. The control input is the force applied on the tank and the overall system consists of two nonlinear…

Optimization and Control · Mathematics 2021-08-26 Iasson Karafyllis , Miroslav Krstic

This work has the goal of briefly surveying some key stabilization techniques for general nonlinear systems, for which, as it is well known, a smooth control Lyapunov function may fail to exist. A general overview of the situation with…

Optimization and Control · Mathematics 2020-07-03 Pavel Osinenko , Patrick Schmidt , Stefan Streif

This paper proposes a novel nonlinear sliding mode state feedback controller for perturbed second-order systems. In analogy to a linear proportional-derivative (PD) feedback control, the proposed nonlinear scheme uses the output of interest…

Optimization and Control · Mathematics 2025-03-25 Michael Ruderman , Denis Efimov

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

Converse optimality theory addresses an optimal control problem conversely where the system is unknown and the value function is chosen. Previous work treated this problem both in continuous and discrete time and non-extensively considered…

Optimization and Control · Mathematics 2022-08-15 Rania Tafat , Thomas Göhrt , Stefan Streif

We construct a robust stabilizing feedback law for the viscous Saint-Venant system of Partial Differential Equations (PDEs) with surface tension and without wall friction. The Saint-Venant system describes the movement of a tank which…

Optimization and Control · Mathematics 2023-01-05 Iasson Karafyllis , Filippos Vokos , Miroslav Krstic

This paper studies the stability of sampled and networked control systems with sampling and communication times governed by probabilistic clocks. The clock models have few restrictions, and can be used to model numerous phenomena such as…

Systems and Control · Computer Science 2014-10-09 Andrew Lamperski

This paper investigates uniform almost sure stability of randomly switched time-varying systems. Mode-dependent indefinite multiple Lyapunov functions (iMLFs) are introduced to assess stability properties of diverse time-varying subsystems.…

Optimization and Control · Mathematics 2025-06-17 Qian Liu , Yong He , Lin Jiang

Lyapunov's theorem provides a fundamental characterization of the stability of dynamical systems. This paper presents a categorical framework for Lyapunov theory, generalizing stability analysis with Lyapunov functions categorically. Core…

Dynamical Systems · Mathematics 2025-08-01 Aaron D. Ames , Joe Moeller , Paulo Tabuada

Considering nonlinear processes which are subject to unknown but measurable disturbances, we provide both stability and feasibility proofs for nonlinear model predictive controllers with abstract updates without the use of stabilizing…

Optimization and Control · Mathematics 2013-09-09 J. Pannek , J. Michael , M. Gerdts

This note studies (practical) asymptotic stability of nonlinear networked control systems whose protocols are not necessarily uniformly globally exponentially stable. In particular, we propose a Lyapunov-based approach to establish…

Systems and Control · Computer Science 2018-10-10 Seyed Hossein Mousavi , Navid Noroozi , Anton H. J. de Ruiter , Roman Geiselhart

This paper presents a distributed Lyapunov-based control framework for achieving both complete and phase synchronization in a class of leader-follower multi-agent systems composed of identical chaotic agents. The proposed approach…

Dynamical Systems · Mathematics 2025-11-25 Marzieh Basiri Abarghoei , Mohammad Reza Ahmadi Zand

Designing a static state-feedback controller subject to structural constraint achieving asymptotic stability is a relevant problem with many applications, including network decentralized control, coordinated control, and sparse feedback…

Optimization and Control · Mathematics 2021-06-03 Francesco Ferrante , Fabrizio Dabbene , Chiara Ravazzi

This paper considers a sampling-based approach to stability verification for piecewise continuous nonlinear systems via Lyapunov functions. Depending on the system dynamics, the candidate Lyapunov function and the set of initial states of…

Systems and Control · Computer Science 2016-09-02 Ruxandra Bobiti , Mircea Lazar

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

This paper introduces a framework for learning a minimum-norm stabilizing controller for a system with unknown dynamics using model-free policy optimization methods. The approach begins by first designing a Control Lyapunov Function (CLF)…

Optimization and Control · Mathematics 2020-10-02 Tyler Westenbroek , Fernando Castaneda , Ayush Agrawal , S. Shankar Sastry , Koushil Sreenath