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This paper develops a Closed-Loop Error Learning Control (CLELC) algorithm for feedback linearizable systems with experimental validation on a mobile robot. Traditional feedback and feedforward controllers are designed based on the nominal…

Robotics · Computer Science 2021-03-17 Erkan Kayacan

Fault diagnosis of rotating machinery plays a important role for the safety and stability of modern industrial systems. However, there is a distribution discrepancy between training data and data of real-world operation scenarios, which…

Sound · Computer Science 2023-10-24 Zhongliang Chen , Zhuofei Huang , Wenxiong Kang

Learning-based controllers leverage nonlinear couplings and enhance transients but seldom offer guarantees under tight input constraints. Robust feedback like sliding-mode control (SMC) provides these guarantees but is conservative in…

Systems and Control · Electrical Eng. & Systems 2026-01-21 Imran Sayyed , Nandan Kumar Sinha

This paper presents and implements an iterative feedback design algorithm for stabilisation of discrete-time switched systems under arbitrary switching regimes. The algorithm seeks state feedback gains so that the closed-loop switching…

Systems and Control · Computer Science 2010-09-13 Hernan Haimovich , Julio H. Braslavsky

This paper outlines a complete methodology for modeling an on-orbit servicing mission scenario and designing a feedback control system for the attitude dynamics that is guaranteed to robustly meet pointing requirements, despite model…

Systems and Control · Electrical Eng. & Systems 2022-09-13 Ricardo Rodrigues , Valentin Preda , Francesco Sanfedino , Daniel Alazard

This paper addresses the problem of safe autonomous navigation in unknown obstacle-filled environments using only local sensory information. We propose a smooth feedback controller derived from an unconstrained penalty-based formulation…

Systems and Control · Electrical Eng. & Systems 2025-11-14 Lyes Smaili , Soulaimane Berkane

Several recent studies attempt to address the biological implausibility of the well-known backpropagation (BP) method. While promising methods such as feedback alignment, direct feedback alignment, and their variants like sign-concordant…

Neural and Evolutionary Computing · Computer Science 2022-05-27 Yukun Yang , Peng Li

With the development of human space exploration, the space environment is gradually filled with abandoned satellite debris and unknown micrometeorites, which will seriously affect capture motion of space robot. Hence, a novel fast…

Robotics · Computer Science 2021-09-02 Wen Yan , Yicheng Liu

Predictive Feedback Control is an easy-to-implement method to stabilize unknown unstable periodic orbits in chaotic dynamical systems. Predictive Feedback Control is severely limited because asymptotic convergence speed decreases with…

Adaptation and Self-Organizing Systems · Physics 2015-03-17 Christian Bick , Christoph Kolodziejski , Marc Timme

Federated learning has emerged recently as a promising solution for distributing machine learning tasks through modern networks of mobile devices. Recent studies have obtained lower bounds on the expected decrease in model loss that is…

We propose a scheme of stabilizing the persistent-current Rabi oscillation based on the flux qubit-resonator-atom hybrid structure. The LC resonator weakly interacts with the flux qubit and maps the persistent-current Rabi oscillation onto…

Atomic Physics · Physics 2018-05-15 Deshui Yu , Rainer Dumke

Robots for physical Human-Robot Collaboration (pHRC) systems need to change their behavior and how they operate in consideration of several factors, such as the performance and intention of a human co-worker and the capabilities of…

Robotics · Computer Science 2023-10-03 Avinash Singh , Dikai Liu , Chin-Teng Lin

The Pyragas method of feedback control has attracted much interest as a method of stabilising unstable periodic orbits in a number of situations. We show that a time-delayed feedback control similar to the Pyragas method can be used to…

Chaotic Dynamics · Physics 2009-11-13 Claire M. Postlethwaite

Controlling instabilities in complex dynamical systems is challenging in scientific and engineering applications. Deep reinforcement learning (DRL) has seen promising results for applications in different scientific applications. The…

Machine Learning · Computer Science 2025-04-09 Luning Sun , Xin-Yang Liu , Siyan Zhao , Aditya Grover , Jian-Xun Wang , Jayaraman J. Thiagarajan

The task of inducing, via continuous static state-feedback control, an asymptotically stable heteroclinic orbit in a nonlinear control system is considered in this paper. The main motivation comes from the problem of ensuring convergence to…

Systems and Control · Electrical Eng. & Systems 2023-02-16 Christian Fredrik Sætre , Anton S. Shiriaev

Weight reduction and low power consumption are key requirements in the next generation of unmanned aerial vehicle (UAV) networks. Employing modulating retro-reflector (MRR)-based free space optical (FSO) technology is an innovative…

Signal Processing · Electrical Eng. & Systems 2022-03-15 Mohammad Taghi Dabiri , Mohsen Rezaee , Leila Mohammadi , Farhang Javaherian , Vahid Yazdanian , Mazen Omar Hasna , Murat Uysal

The aim of this paper is to present a new fast-convergent numerically stable space-time adaptive processing (STAP) algorithm derived using a novel technique of feedback orthogonalization. The main advantages of this approach lie in its…

Instrumentation and Methods for Astrophysics · Physics 2010-08-26 Vasily A. Khlebnikov , Kristian Zarb Adami

This paper introduces a method for efficiently updating a nominal stabilizing static output feedback (SOF) controller in perturbed linear systems. As operating points and state-space matrices change in dynamic systems, accommodating updates…

Systems and Control · Electrical Eng. & Systems 2025-12-03 MirSaleh Bahavarnia , Ahmad F. Taha

Asynchronous federated learning mitigates the inefficiency of conventional synchronous aggregation by integrating updates as they arrive and adjusting their influence based on staleness. Due to asynchrony and data heterogeneity, learning…

Machine Learning · Computer Science 2025-02-27 Jiayun Zhang , Shuheng Li , Haiyu Huang , Xiaofan Yu , Rajesh K. Gupta , Jingbo Shang