Results 171 to 180 of about 16,024 (227)

Distributed Cooperative LQR Design for Multi-Input Linear Systems

IEEE Transactions on Control of Network Systems, 2023
In this article, a cooperative linear quadratic regulator (LQR) problem is investigated for multi-input systems, where each input is generated by an agent in a network.
Peihu Duan, Lidong He, Z. Duan, Ling Shi
semanticscholar   +1 more source

Motion Planning and Pose Control for Flexible Spacecraft Using Enhanced LQR-RRT*

IEEE Transactions on Aerospace and Electronic Systems, 2023
The primary difficulty of on-orbit services is autonomous real-time motion planning, especially considering collision avoidance among complex modulars.
Xilin Zhong, Zhengtao Wei, Ti Chen
semanticscholar   +1 more source

A convex approach to robust LQR

2020 59th IEEE Conference on Decision and Control (CDC), 2020
In this paper, we propose some new convex strategies for robust optimal control. In particular, we treat the problem of designing finite-horizon linear quadratic regulator (LQR) for uncertain discrete-time systems focusing on minimax strategies. A time-invariant linear control law is obtained just solving sequentially two convex optimization problems ...
Scampicchio A., Pillonetto G.
openaire   +2 more sources

LQR-CBF-RRT*: Safe and Optimal Motion Planning

American Control Conference, 2023
We present LQR-CBF-RRT*, an incremental sampling-based algorithm for offline motion planning. Our framework leverages the strength of Control Barrier Functions (CBFs) and Linear Quadratic Regulators (LQR) to generate safety-critical and optimal ...
Guangtao Yang, Mingyu Cai, A. Ahmad, Amanda Prorok, Roberto Tron, C. Belta   +5 more
semanticscholar   +1 more source

On LQR control with asynchronous clocks

IEEE Conference on Decision and Control and European Control Conference, 2011
We consider LQR control for a scalar system when the sensor, controller, and actuator all have their own clocks that may drift apart from each other. We consider both an affine and a quadratic clock model. For a quadratic cost function, we analyze the loss of performance incurred as a function of how asynchronous the clocks are.
Rahul Singh 0001, Vijay Gupta 0001
openaire   +1 more source

Bounded-Error LQR-Trees

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019
We present a feedback motion planning algorithm, Bounded-Error LQR-Trees, that leverages reinforcement learning theory to find a policy with a bounded amount of error. The algorithm composes locally valid linear-quadratic regulators (LQR) into a nonlinear controller, similar to how LQR-Trees constructs its policy, but minimizes the cost of the ...
Barrett Ames, George Dimitri Konidaris
openaire   +1 more source

Localized LQR control with actuator regularization

2016 American Control Conference (ACC), 2016
In previous work, we posed and solved the localized linear quadratic regulator (LLQR) problem - a LLQR controller is one that limits the propagation of dynamics to user-specified subsets of the global system. The advantages of taking this approach are tangible, as we show that this allows the controller to be synthesized and implemented in a scalable ...
Wang, Yuh-Shyang, Matni, Nikolai, Doyle, John C.   +2 more
openaire   +2 more sources

Regularization for Covariance Parameterization of Direct Data-Driven LQR Control

IEEE Control Systems Letters
As the benchmark of data-driven control methods, the linear quadratic regulator (LQR) problem has gained significant attention. A growing trend is direct LQR design, which finds the optimal LQR gain directly from raw data and bypassing system ...
Feiran Zhao, Alessandro Chiuso, F. Dörfler   +2 more
semanticscholar   +1 more source

LQR via First Order Flows

2020 American Control Conference (ACC), 2020
We consider the Linear-Quadratic-Regulator (LQR) problem in terms of optimizing a real-valued matrix function over the set of feedback gains. Such a setup facilitates examining the implications of a natural initial-state independent formulation of LQR in designing first order algorithms.
Jingjing Bu, Afshin Mesbahi, Mehran Mesbahi   +2 more
openaire   +1 more source

Intelligent vehicle lateral control strategy research based on feedforward + predictive LQR algorithm with GA optimisation and PID compensation

Scientific Reports
Targeting the lateral motion control problem in the intelligent vehicle autopilot structural system, this paper proposes a feedforward + predictive LQR algorithm for lateral motion control based on Genetic Algorithm (GA) parameter optimisation and PID ...
Zhu-an Zheng, Zimo Ye, Xiangyu Zheng
semanticscholar   +1 more source