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Linear Quadratic Regulator: II. Robust Formulations
Automation and Remote Control, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mikhail V. Khlebnikov +1 more
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The Inconsistent Linear Quadratic Regulator
2021In this chapter we study a simple time-inconsistent version of the linear quadratic regulator in continuous time. Time inconsistency enters through an explicit dependence on the initial state for the final quadratic term. Loosely speaking, we want to control a system such that the final state is close to the initial point while at the same time keeping
Tomas Björk +2 more
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Random search for learning the linear quadratic regulator
2020 American Control Conference (ACC), 2020Many emerging applications involve control of systems with unknown dynamics. As a result, model-free random search techniques that directly search over the space of parameters have become popular. These algorithms often exhibit a competitive sample complexity compared to state-of- the-art techniques.
Hesameddin Mohammadi +2 more
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Linear–Quadratic Regulator Problems
1995Abstract The “linear-quadratic regulator” (LQR) problem of optimal control has probably provided the greatest single stimulus for investigation of matrix Riccati equations in differential, difference, and algebraic forms. In this chapter the continuous and discrete LQR problems are to be outlined and then the solutions of these ...
Peter Lancaster, Leiba Rodman
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Effect of nonlinearity on linear quadratic regulator performance
2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004Two new local measure of nonlinearity are introduced to quantify the sensitivity of controller stability and performance for linear controllers operating on a nonlinear plant. The measure quantifies the departures from optimality of locally linear quadratic regulators.
Martin Guay, J. Fraber Forbes
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Understand direct NDP with linear quadratic regulation
Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004., 2005This work falls into the general area of approximate dynamic programming. Direct NDP designs are further analyzed using classic control-theoretic sensitivity arguments. The relationship between direct NDP and LQR designs are discussed due to their resemblances in system performance functions.
Lei Yang 0001 +2 more
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Dynamic Gain Adaptation in Linear Quadratic Regulators
IEEE Transactions on Automatic ControlzbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Reduced explicit constrained linear quadratic regulators
IEEE Transactions on Automatic Control, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon
SIAM Journal on Control and Optimization, 2021Ben Hambly, Renyuan Xu
exaly