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Bounding is one of the important gaits in quadrupedal locomotion for negotiating obstacles. The authors proposed an effective approach that can learn robust bounding gaits more efficiently despite its large variation in dynamic body…

Robotics · Computer Science 2023-10-31 Zhicheng Wang , Anqiao Li , Yixiao Zheng , Anhuan Xie , Zhibin Li , Jun Wu , Qiuguo Zhu

The increasing demands for high accuracy in mechatronic systems necessitate the incorporation of parameter variations in feedforward control. The aim of this paper is to develop a data-driven approach for direct learning of…

Systems and Control · Electrical Eng. & Systems 2025-05-14 Max van Haren , Lennart Blanken , Tom Oomen

Limitations of the delayed feedback control and of its extended versions have been fully treated in the literature. The oscillating delayed feedback control appears as a promising scheme to overcome this problem. In this work, two methods…

Dynamical Systems · Mathematics 2018-05-25 Verónica E. Pastor , Graciela González

Predictor feedback designs are critical for delay-compensating controllers in nonlinear systems. However, these designs are limited in practical applications as predictors cannot be directly implemented, but require numerical approximation…

Systems and Control · Electrical Eng. & Systems 2025-06-03 Luke Bhan , Peijia Qin , Miroslav Krstic , Yuanyuan Shi

Control of underactuated dynamical systems has been studied for decades in robotics, and is now emerging in other fields such as neuroscience. Most of the advances have been in model based control theory, which has limitations when the…

Optimization and Control · Mathematics 2020-06-30 Bharat Monga , Jeff Moehlis

Deep reinforcement learning (RL) has shown immense potential for learning to control systems through data alone. However, one challenge deep RL faces is that the full state of the system is often not observable. When this is the case, the…

Machine Learning · Computer Science 2023-10-27 Ian Char , Jeff Schneider

In many machine learning applications, there are multiple decision-makers involved, both automated and human. The interaction between these agents often goes unaddressed in algorithmic development. In this work, we explore a simple version…

Machine Learning · Statistics 2018-09-10 David Madras , Toniann Pitassi , Richard Zemel

This study proposes a delay-compensated feedback controller based on proximal policy optimization (PPO) reinforcement learning to stabilize traffic flow in the congested regime by manipulating the time-gap of adaptive cruise…

Artificial Intelligence · Computer Science 2023-01-18 Shurong Mo , Nailong Wu , Jie Qi , Anqi Pan , Zhiguang Feng , Huaicheng Yan , Yueying Wang

The control of devices with limited input always bring attention to solve by research due to its difficulty and non-trival solution. For instance, the inverted pendulum is benchmarking problem in control theory and machine learning. In this…

Robotics · Computer Science 2026-03-16 Pawel Marczewski , Paulina Superczynska , Jakub Bernat , Szymon Szczesny

A general scheme for construction of dynamical systems able to learn generation of the desired kinds of dynamics through adjustment of their internal structure is proposed. The scheme involves intrinsic time-delayed feedback to steer the…

Adaptation and Self-Organizing Systems · Physics 2015-06-22 Pablo Kaluza , Alexander S. Mikhailov

Inverted landing in a rapid and robust manner is a challenging feat for aerial robots, especially while depending entirely on onboard sensing and computation. In spite of this, this feat is routinely performed by biological fliers such as…

Robotics · Computer Science 2023-04-26 Bryan Habas , Jack W. Langelaan , Bo Cheng

Feedback alignment and related weight-transport-free algorithms are often proposed as biologically plausible alternatives to backpropagation, yet they are typically formulated in discrete phases with implicitly synchronized forward and…

Machine Learning · Computer Science 2026-03-03 Marc Gong Bacvanski , Liu Ziyin , Tomaso Poggio

We present an iterative approach for planning and controlling motions of underactuated robots with uncertain dynamics. At its core, there is a learning process which estimates the perturbations induced by the model uncertainty on the active…

PUBLISHED ON IEEE/ASME TRANSACTIONS ON MECHATRONICS, DOI: 10.1109/TMECH.2021.3100150. Ideally, accurate sensor measurements are needed to achieve a good performance in the closed-loop control of mechatronic systems. As a consequence, sensor…

Systems and Control · Electrical Eng. & Systems 2021-12-02 Daulet Baimukashev , Bexultan Rakhim , Matteo Rubagotti , Huseyin Atakan Varol

Feedforward control is essential to achieving good tracking performance in positioning systems. The aim of this paper is to develop an identification strategy for inverse models of systems with nonlinear dynamics of unknown structure using…

Systems and Control · Electrical Eng. & Systems 2022-02-10 Max van Meer , Maurice Poot , Jim Portegies , Tom Oomen

Adaptive control can be applied to robotic systems with parameter uncertainties, but improving its performance is usually difficult, especially under discontinuous friction. Inspired by the human motor learning control mechanism, an…

Robotics · Computer Science 2024-01-22 Yongping Pan , Kai Guo , Tairen Sun , Mohamed Darouach

Locomotion of legged machines faces the problems of model complexity and computational costs. Algorithms based on complex models and/or reinforcement learning exist to solve the walking control task. In this project, we aim to develop a…

Robotics · Computer Science 2018-05-17 Kendeas Theofanous

Besides parametric uncertainties and disturbances, the unmodeled dynamics and time delay at the input are often present in practical systems, which cannot be ignored in some cases. This paper aims to solve output feedback tracking control…

Systems and Control · Computer Science 2020-03-10 Quan Quan , Hai Lin , Kai-Yuan Cai

We study the stability of unstable steady states in scalar retarded time-delayed systems subjected to a variable-delay feedback control. The important aspect of such a control problem is that time-delayed systems are already…

Chaotic Dynamics · Physics 2010-07-08 Aleksandar Gjurchinovski , Viktor Urumov

This work addresses fundamental issues related to the structure and conditioning of linear time-delayed models of non-linear dynamics on an attractor. While this approach has been well-studied in the asymptotic sense (e.g. for infinite…

Dynamical Systems · Mathematics 2020-07-27 Shaowu Pan , Karthik Duraisamy