Results 181 to 190 of about 16,024 (227)

A closed-loop directional dynamics control with LQR active trailer steering for articulated heavy vehicle

Proceedings of the Institution of mechanical engineers. Part D, journal of automobile engineering, 2022
To improve the directional performance of articulated heavy vehicles (AHV), three previewed points driver model and LQR active trailer steering (ATS) strategy are proposed and examined using closed-loop driver/vehicle dynamics simulation.
Zhao-wen Deng, Yonghui Jin, Wei Gao, B. Wang   +3 more
semanticscholar   +1 more source

Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for the Model-free LQR

Conference on Learning for Dynamics & Control
We investigate the problem of learning linear quadratic regulators (LQR) in a multi-task, heterogeneous, and model-free setting. We characterize the stability and personalization guarantees of a policy gradient-based (PG) model-agnostic meta-learning ...
Leonardo F. Toso, Donglin Zhan, James Anderson, Han Wang   +3 more
semanticscholar   +1 more source

A Kalman-Koopman LQR Control Approach to Robotic Systems

IEEE transactions on industrial electronics (1982. Print)
This article presents a Kalman–Koopman linear quadratic regulator (KKLQR) control approach to robotic systems. In the proposed approach, an optimal Koopman modeling method based on neural networks, in which continuous Koopman eigenfunctions are ...
Dongdong Zhao, Xiaodi Yang, Yichang Li, Li Xu, Jinhua She, Shi Yan   +5 more
semanticscholar   +1 more source

Experimental Validation of LQR Weight Optimization Using Bat Algorithm Applied to Vibration Control of Vehicle Suspension System

Journal of the Institution of Electronics and Telecommunication Engineers, 2022
To deal with multiple constraints of vehicle active suspension system (ASS) including road handling and passenger safety, this paper presents an optimal linear quadratic regulator (LQR) approach which employs bat algorithm (BA) for selection of optimal ...
T. Yuvapriya, P. Lakshmi, Vinodh Kumar Elumalai   +2 more
semanticscholar   +1 more source

Tuning LQR Controllers: A Sensitivity-Based Approach

IEEE Control Systems Letters, 2022
We introduce an approach to efficiently tune LQR controllers for linear time-invariant systems to match a prescribed closed-loop behavior, such as the one given by a reference model.
Daniele Masti, Mario Zanon, A. Bemporad
semanticscholar   +1 more source

Adaptive LQR Path Tracking Control for 4WS Electric Vehicles Based on Genetic Algorithm

2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI), 2022
The four-wheel steering electric vehicles are considered as ideal autonomous vehicles, and the linear quadratic regulator (LQR) is widely adopted in path tracking control. The choice of $Q$ and $R$ matrices is an essential problem in LQR design. However,
Ao Lu, Ziwang Lu, Runfeng Li, Guangyu Tian   +3 more
semanticscholar   +1 more source

LQR-based Balance Control of Two-wheeled Legged Robot

Cybersecurity and Cyberforensics Conference, 2022
Recently, the research of wheel-legged robot (WLR) has become a hot spot. WLR has fast speed, high efficiency and strong adaptability to terrain, which makes full use of the advantages of wheeled robots and leg robots.
Jinyang Dong, R. Liu, Biao Lu, Xian Guo, Huawang Liu   +4 more
semanticscholar   +1 more source

LQR optimization of linear system switching

IEEE Transactions on Automatic Control, 2002
Considers offline optimization of a switching sequence for a given finite set of linear control systems, together with joint optimization of control laws. A linear quadratic full information criterion is optimized and dynamic programming is used to find an optimal switching sequence and control law.
Bo Lincoln, Bo Bernhardsson
openaire   +1 more source

Path Tracking Motion Control Method Of Tracked Robot Based On Improved LQR Control

Cybersecurity and Cyberforensics Conference, 2022
In order to enhance the trajectory tracking control performance of tracked mobile robot, an improved LQR lateral motion control method is proposed. Firstly, the robot tracking error kinematics model is constructed by using Lagrange function method, and ...
Jianyun Ni, Yong Wang, Hao Li, Helei Du
semanticscholar   +1 more source

Autonomous Driving Motion Planning With Constrained Iterative LQR

IEEE Transactions on Intelligent Vehicles, 2019
Motion planning is a core technique for autonomous driving. Nowadays, there still exists a lot of challenges in motion planning for autonomous driving in complicated environments due to: 1) the need of both spatial and temporal planning in highly dynamic
Jianyu Chen, Wei Zhan, M. Tomizuka
semanticscholar   +1 more source