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We study the implementation of a weak multiple delayed feedback for controlling coherence of chaotic oscillations. The specific system we treat is the Lorenz system with classical set of parameters. There are two reasons behind the interest…

Statistical Mechanics · Physics 2009-12-03 Denis S. Goldobin , Elizaveta V. Shklyaeva

This paper presents a deep learning based model predictive control algorithm for control affine nonlinear discrete time systems with matched and bounded state dependent uncertainties of unknown structure. Since the structure of…

Optimization and Control · Mathematics 2021-09-28 Prabhat K. Mishra , Mateus V. Gasparino , Andres E. B. Velsasquez , Girish Chowdhary

An integral extension of state-feedback controllers for linear time-varying plants is proposed, which preserves performance of the nominal controller in the unperturbed case. Similar to time-invariant state feedback with integral action,…

Systems and Control · Electrical Eng. & Systems 2021-12-28 Richard Seeber , Markus Tranninger

Underwater robots in shallow waters usually suffer from strong wave forces, which may frequently exceed robot's control constraints. Learning-based controllers are suitable for disturbance rejection control, but the excessive disturbances…

Robotics · Computer Science 2020-07-30 Tianming Wang , Wenjie Lu , Huan Yu , Dikai Liu

We propose a novel feedback controller for a class of uncertain higher-order nonlinear systems, subject to delays in both state measurement and control input signals. Building on the prescribed performance control framework, a…

Optimization and Control · Mathematics 2025-09-11 Thomas Berger , Lampros N. Bikas , Jan Hachmeister , George A. Rovithakis

Control of systems where the information between the controller, actuator, and sensor can be lost or delayed can be challenging with respect to stability and performance. One way to overcome the resulting problems is the use of prediction…

Optimization and Control · Mathematics 2011-09-27 Rolf Findeisen , Lars Grüne , Jürgen Pannek , Paolo Varutti

In this work we address the problem of the online robust control of nonlinear dynamical systems perturbed by disturbance. We study the problem of attenuation of the total cost over a duration $T$ in response to the disturbances. We consider…

Systems and Control · Electrical Eng. & Systems 2022-09-14 Deepan Muthirayan , Pramod P. Khargonekar

We consider the problem of output feedback regulationfor a linear first-order hyperbolic system with collocatedinput and output in presence of a general class of disturbancesand noise. The proposed control law is designed through…

Analysis of PDEs · Mathematics 2017-10-20 Pierre-Olivier Lamare , Jean Auriol , Florent Di Meglio , Ulf Jakob F. Aarsnes

Data-driven direct methods are still growing in popularity almost three decades after they were introduced. These methods use data collected from the process to identify optimal controller's parameters with little knowledge about the…

Systems and Control · Electrical Eng. & Systems 2023-07-06 Róger W. P. da Silva , Diego Eckhard

Inverter-dominated microgrids are quickly becoming a key building block of future power systems. They rely on centralized controllers that can provide reliability and resiliency in extreme events. Nonetheless, communication failures due to…

Systems and Control · Electrical Eng. & Systems 2023-07-11 Siddharth Bhela , Abhishek Banerjee , Ulrich Muenz , Joachim Bamberger

We present a new direct adaptive control approach for nonlinear systems with unmatched and matched uncertainties. The method relies on adjusting the adaptation gains of individual unmatched parameters whose adaptation transients would…

Systems and Control · Electrical Eng. & Systems 2023-11-10 Brett T. Lopez , Jean-Jacques Slotine

In this paper, we investigate the optimal output tracking problem for linear discrete-time systems with unknown dynamics using reinforcement learning and robust output regulation theory. This output tracking problem only allows to utilize…

Dynamical Systems · Mathematics 2021-01-22 Ci Chen , Lihua Xie , Yi Jiang , Kan Xie , Shengli Xie

This paper focuses on the consensus and formation problems of multiagent systems under unknown persistent disturbances. Specifically, we propose a novel method that combines an existing consensus (or formation) algorithm with a new…

Optimization and Control · Mathematics 2013-10-15 Tansel Yucelen , Magnus Egerstedt

This paper studies the synchronization problem of second-order nonlinear multi-agent systems with intermittent communication in the presence of irregular communication delays and possible information loss. The control objective is to steer…

Optimization and Control · Mathematics 2015-05-07 Abdelkader Abdessameud , Ilia G. Polushin , Abdelhamid Tayebi

A desirable property in fault-tolerant controllers is adaptability to system changes as they evolve during systems operations. An adaptive controller does not require optimal control policies to be enumerated for possible faults. Instead it…

Systems and Control · Electrical Eng. & Systems 2020-08-12 Ibrahim Ahmed , Hamed Khorasgani , Gautam Biswas

In this paper, adaptive set-point regulation controllers for discrete-time nonlinear systems are constructed. The system to be controlled is assumed to have a parametric uncertainty, and an excitation signal is used in order to obtain the…

Optimization and Control · Mathematics 2015-05-25 Shigeru Hanba

This paper investigates the problem of resilient global practical fixed-time cooperative output regulation of uncertain nonlinear multi-agent systems subject to denial-of-service attacks. A novel distributed resilient adaptive fixed-time…

Systems and Control · Electrical Eng. & Systems 2025-09-11 Wenji Cao , Lu Liu , Zehua Ye , Dan Zhang , Gang Feng

In this paper, we restudy how to modify the model-free adaptive control (MFAC) to reject the disturbance both in single-input single-output (SISO) systems and multiple-input multiple-output (MIMO) systems, with the aim to pave the way for…

Systems and Control · Electrical Eng. & Systems 2023-12-07 Feilong Zhang

We consider control in linear time-varying dynamical systems from the perspective of regret minimization. Unlike most prior work in this area, we focus on the problem of designing an online controller which minimizes regret against the best…

Machine Learning · Computer Science 2021-02-03 Gautam Goel , Babak Hassibi

We study the control of a linear dynamical system with adversarial disturbances (as opposed to statistical noise). The objective we consider is one of regret: we desire an online control procedure that can do nearly as well as that of a…

Machine Learning · Computer Science 2019-02-26 Naman Agarwal , Brian Bullins , Elad Hazan , Sham M. Kakade , Karan Singh