Results 181 to 190 of about 12,702 (221)
Leveraging Innovative Electronic Health Record Data to Characterize Social Determinants of Health Among Survivors of Cancer in Persistent Poverty Areas: Cross-Sectional Study. [PDF]
JMIR CancerTanaka S +9 more
europepmc +1 more source
Analysis of Control System Models With Conventional LQR and Fuzzy LQR Controller
Procedia Computer Science, 2019 Abstract Linear quadratic LQR and fuzzy FLC+LQR controllers are analyzed. It is shown that under the same conditions, the fuzzy FLC+LQR controller has a much higher speed than the LQR controller.
E S Duvanov, Y I Kudinov, F F Pashchenko
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PID, LQR and LQR-PID on a Quadcopter Platform [PDF]
2013 International Conference on Informatics, Electronics and Vision (ICIEV), 2013 This paper aims to present a comparison between different controllers to be used in a dynamic model of a quadcopter platform. The controllers assumed in this work are an ITAE tuned PID, a classic LQR controller and a PID tuned with a LQR loop. The results were obtained through simulations for 10 different attitudes of the quadcopter, however, in this ...
Paulo E Santos
exaly +2 more sources
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A convex approach to robust LQR
2020 59th IEEE Conference on Decision and Control (CDC), 2020In 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.
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On LQR control with asynchronous clocks
IEEE Conference on Decision and Control and European Control Conference, 2011We 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
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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
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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
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Localized LQR control with actuator regularization
2016 American Control Conference (ACC), 2016In 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 +2 more
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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 +2 more
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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 +2 more
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LQR optimization of linear system switching
IEEE Transactions on Automatic Control, 2002Considers 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
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LQR for State-Bounded Structural Control
Journal of Dynamic Systems, Measurement, and Control, 1996In order to prevent structural damages, it is more important to bound the vibration amplitude than to reduce the vibration energy. However, in the performance index for linear quadratic regulator (LQR), the instantaneous amplitude of vibration is not minimized.
Chuang, C.-H., Wu, D.-N., Wang, Q.
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