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This study evaluates the application of a discrete action space reinforcement learning method (Q-learning) to the continuous control problem of robot inverted pendulum balancing. To speed up the learning process and to overcome technical…

Robotics · Computer Science 2023-12-06 Mohammad Safeea , Pedro Neto

It is well-known that linear quadratic regulators (LQR) enjoy guaranteed stability margins, whereas linear quadratic Gaussian regulators (LQG) do not. In this letter, we consider systems and compensators defined over directed acyclic…

Systems and Control · Electrical Eng. & Systems 2023-05-29 Mruganka Kashyap , Laurent Lessard

We develop a feedback strategy based on optimal quantum feedback control for Gaussian systems to maximise the likelihood of steady-state entanglement detection between two directly interacting masses. We employ linear quadratic Gaussian…

This paper presents a new framework for controller robustness verification with respect to F-16 aircraft's closed-loop performance in longitudinal flight. We compare the state regulation performance of a linear quadratic regulator (LQR) and…

Systems and Control · Computer Science 2014-02-04 Abhishek Halder , Kooktae Lee , Raktim Bhattacharya

Controlled Lagrangian and matching techniques are developed for the stabilization of relative equilibria and equilibria of discrete mechanical systems with symmetry as well as broken symmetry. Interesting new phenomena arise in the…

Optimization and Control · Mathematics 2007-05-23 Anthony M. Bloch , Melvin Leok , Jerrold E. Marsden , Dmitry V. Zenkov

The purpose of this paper is to study the mixed linear quadratic Gaussian (LQG) and $H_\infty$ optimal control problem for linear quantum stochastic systems, where the controller itself is also a quantum system, often referred to as…

Quantum Physics · Physics 2016-11-15 Lei Cui , Zhiyuan Dong , Guofeng Zhang , Heung Wing Joseph Lee

This paper presents a novel direct data-driven control framework for solving the linear quadratic regulator (LQR) under disturbances and noisy state measurements. The system dynamics are assumed unknown, and the LQR solution is learned…

Systems and Control · Electrical Eng. & Systems 2025-05-13 Ramin Esmzad , Gokul S. Sankar , Teawon Han , Hamidreza Modares

This paper presents a one-shot learning approach with performance and robustness guarantees for the linear quadratic regulator (LQR) control of stochastic linear systems. Even though data-based LQR control has been widely considered,…

Systems and Control · Electrical Eng. & Systems 2024-10-29 Ramin Esmzad , Hamidreza Modares

In this paper, a novel recurrent adaptive backstepping optimal control strategy for a single inverted pendulum system is studied. By this method, an inverted pendulum is stabilized using projection recurrent neural network-based adaptive…

Systems and Control · Electrical Eng. & Systems 2021-10-20 Mohammad Sarbaz

A double inverted pendulum plant has been in the domain of control researchers as an established model for studies on stability. The stability of such as a system taking the linearized plant dynamics has yielded satisfactory results by many…

Systems and Control · Computer Science 2015-11-10 Kavirayani Srikanth , Gundavarapu Nagesh Kumar

We study the linear quadratic Gaussian (LQG) control problem, in which the controller's observation of the system state is such that a desired cost is unattainable. To achieve the desired LQG cost, we introduce a communication link from the…

Optimization and Control · Mathematics 2021-09-28 Oron Sabag , Peida Tian , Victoria Kostina , Babak Hassibi

In this paper, we propose a novel dynamic state-feedback controller for polytopic linear parameter-varying (LPV) systems with constant input matrix. The controller employs a projected gradient flow method to continuously improve its control…

Systems and Control · Electrical Eng. & Systems 2025-05-29 Armin Gießler , Felix Strehle , Jochen Illerhaus , Sören Hohmann

Inertial Navigation Systems (INS) are algorithms that fuse inertial measurements of angular velocity and specific acceleration with supplementary sensors including GNSS and magnetometers to estimate the position, velocity and attitude, or…

Systems and Control · Electrical Eng. & Systems 2023-08-23 Pieter van Goor , Tarek Hamel , Robert Mahony

In this paper, a dynamic antiwindup compensator design is proposed which augments the main controller and guarantees robust performance in the event of input saturation. This is a two stage process in which first a robust optimal controller…

Systems and Control · Computer Science 2015-03-19 Obaid ur Rehman , Ian R. Petersen , Baris Fidan

We propose and analyse a new methodology based on linear-quadratic regulation (LQR) for stabilising falling liquid films via blowing and suction at the base. LQR methods enable rapidly responding feedback control by precomputing a gain…

Optimization and Control · Mathematics 2023-07-11 Oscar A. Holroyd , Radu Cimpeanu , Susana N. Gomes

Time delays due to signal latency, computational complexity, and sensor-denied environments, pose a critical challenge in both engineered and biological control systems. In this work, we investigate biologically inspired strategies to…

Systems and Control · Electrical Eng. & Systems 2019-12-12 Thomas L. Mohren , Thomas L. Daniel , Steven L. Brunton

This paper studies the partially observed stochastic optimal control problem for systems with state dynamics governed by partial differential equations (PDEs) that leads to an extremely large problem. First, an open-loop deterministic…

Optimization and Control · Mathematics 2017-11-06 Dan Yu , Mohammadhussein Rafieisakhaei , Suman Chakravorty

Title: Global stabilization of control nonlinear system "inverted pendulum on a cart" using method of two Lyapunov functions Authors: B. L. Mazov (Nizhny Novgorod Technical University) Comments: 10 pages Subj-class: Dynamical Systems…

Dynamical Systems · Mathematics 2007-05-23 B. L. Mazov

This paper investigates the robot state estimation problem within a non-inertial environment. The proposed state estimation approach relaxes the common assumption of static ground in the system modeling. The process and measurement models…

Robotics · Computer Science 2024-03-26 Zijian He , Sangli Teng , Tzu-Yuan Lin , Maani Ghaffari , Yan Gu

We propose a new framework to design controllers for high-dimensional nonlinear systems. The control is designed through the iterative linear quadratic regulator (ILQR), an algorithm that computes control by iteratively applying the linear…

Optimization and Control · Mathematics 2021-10-12 Yizhe Huang , Boris Kramer
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