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We introduce discontinuous solutions to nonlinear impulsive control systems with state time delays in the dynamics and derive necessary optimality conditions in the form of a Maximum Principle for associated optimal control problems. In the…

Optimization and Control · Mathematics 2024-07-11 Giovanni Fusco , Monica Motta , Richard Vinter

A new method for solving optimal tracking control of linear quadratic time-varying systems with multiple time delays in state and input variables and with combined constraints is presented in this paper. By using the relations of Chebyshev…

Optimization and Control · Mathematics 2018-02-16 Iman Malmir

In this paper, we consider optimal control problems derived by stochastic systems with delay, where control domains are non-convex and the diffusion coefficients depend on control variables. By an estimate of the integral of…

Optimization and Control · Mathematics 2022-10-25 Qixia Zhang

Time delays are ubiquitous in industrial processes, and they must be accounted for when designing control algorithms because they have a significant effect on the process dynamics. Therefore, in this work, we propose a simultaneous approach…

Optimization and Control · Mathematics 2024-10-22 Tobias K. S. Ritschel

In this article, we consider a fundamental decentralized optimal control problem, which we call the two-player problem. Two subsystems are interconnected in a nested information pattern, and output feedback controllers must be designed for…

Systems and Control · Computer Science 2015-07-10 Laurent Lessard , Sanjay Lall

In this paper, we study some control problems that derive from time optimal control of coupled spin dynamics in NMR spectroscopy and quantum information and computation. Time optimal control helps to minimize relaxation losses. The ability…

Quantum Physics · Physics 2017-09-05 Navin Khaneja

Practical adaptive control implementations where human pilots coexist in the loop are still uncommon, despite their success in handling uncertain dynamical systems. This is owing to their special nonlinear characteristics which lead to…

Systems and Control · Electrical Eng. & Systems 2022-08-30 Abdullah Habboush , Yildiray Yildiz

Model-based controllers can offer strong guarantees on stability and convergence by relying on physically accurate dynamic models. However, these are rarely available for high-dimensional mechanical systems such as deformable objects or…

Robotics · Computer Science 2026-02-10 Katharina Friedl , Noémie Jaquier , Seungyeon Kim , Jens Lundell , Danica Kragic

This paper presents a reinforcement learning-based neuroadaptive control framework for robotic manipulators operating under deferred constraints. The proposed approach improves traditional barrier Lyapunov functions by introducing a smooth…

Robotics · Computer Science 2025-03-20 Hamed Rahimi Nohooji , Abolfazl Zaraki , Holger Voos

The duality of sensory inference and motor control has been known since the 1960s and has recently been recognized as the commonality in computations required for the posterior distributions in Bayesian inference and the value functions in…

Neurons and Cognition · Quantitative Biology 2021-10-12 Kenji Doya

We consider state-feedback predictor-based control of networked control systems with large time-varying communication delays. We show that even a small controller-to-actuators delay uncertainty may lead to a non-small residual error in a…

Optimization and Control · Mathematics 2016-11-07 A. Selivanov , E. Fridman

We consider a single theta neuron with delayed self-feedback in the form of a Dirac delta function in time. Because the dynamics of a theta neuron on its own can be solved explicitly -- it is either excitable or shows self-pulsations -- we…

Dynamical Systems · Mathematics 2023-01-11 Carlo R. Laing , Bernd Krauskopf

Robots and control systems rely upon precise timing of sensors and actuators in order to operate intelligently. We present a functioning hexapod robot that walks with a dual tripod gait; each tripod is actuated using its own local…

Robotics · Computer Science 2018-08-27 James Fang , Dinesh Parimi , Arjun Dhindsa , Craig B. Schindler , Kristofer S. J. Pister

This paper describes the evolution of controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track. Five different controller architectures were compared, based on neural networks, force fields…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Julian Togelius , Simon M. Lucas

Living organisms interact with their surroundings in a closed-loop fashion, where sensory inputs dictate the initiation and termination of behaviours. Even simple animals are able to develop and execute complex plans, which has not yet been…

Robotics · Computer Science 2025-01-30 Giulia Lafratta , Bernd Porr , Christopher Chandler , Alice Miller

We study the throughput-vs-delay trade-off in an overlay multi-channel single-secondary-user cognitive radio system. Due to the limited sensing capabilities of the cognitive radio user, channels are sensed sequentially. Maximizing the…

Information Theory · Computer Science 2016-12-28 Ahmed Ewaisha , Cihan Tepedelenlioglu

Fast and precise robot motion is needed in certain applications such as electronic manufacturing, additive manufacturing and assembly. Most industrial robot motion controllers allow externally commanded motion profile, but the trajectory…

Robotics · Computer Science 2019-03-06 Shuyang Chen , John T. Wen

We consider a type of optimal switching problems with non-uniform execution delays and ramping. Such problems frequently occur in the operation of economical and engineering systems. We first provide a solution to the problem by applying a…

Optimization and Control · Mathematics 2017-02-15 Magnus Perninge

Control systems are at the core of every real-world robot. They are deployed in an ever-increasing number of applications, ranging from autonomous racing and search-and-rescue missions to industrial inspections and space exploration. To…

Robotics · Computer Science 2024-07-03 Yunlong Song , Davide Scaramuzza

We study the problem of generating control laws for systems with unknown dynamics. Our approach is to represent the controller and the value function with neural networks, and to train them using loss functions adapted from the…

Robotics · Computer Science 2023-02-21 Selim Engin , Volkan Isler