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The Linear Quadratic Regulator
2021In order to illustrate the use of dynamic programming and the Bellman equation we now consider a classical engineering problem: The linear quadratic regulator or LQR. The LQR is a well-known design technique in which a process or machine has its settings optimized by minimizing a quadratic cost function. The cost function is often defined as the sum of
Tomas Björk +2 more
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Model-Free Linear Quadratic Regulator
2021We review recent results on the convergence and sample complexity of the random search method for the infinite-horizon linear quadratic regulator (LQR) problem with unknown model parameters. This method directly searches over the space of stabilizing feedback gain matrices and, in spite of the lack of convexity, it converges to the globally optimal LQR
Hesameddin Mohammadi +2 more
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Linear Quadratic Regulator: II. Robust Formulations
Automation and Remote Control, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Khlebnikov, M. V., Shcherbakov, P. S.
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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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Regression-Based Linear Quadratic Regulator
2018 IEEE International Conference on Robotics and Automation (ICRA), 2018We present the Regression-based Linear Quadratic Regulator (R-LQR), a new approach for determining locally-optimal control feedback policies for robots with non-linear dynamics and non-quadratic cost functions. Our proposal uses a free-derivative algorithm based on local quadratic regressions to obtain the robot motion policy.
Hugo Carlos +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 problems ...
Peter Lancaster, Leiba Rodman
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Fractional Order Linear Quadratic Regulator
2008 IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications, 2008In this paper, we formulate the fractional linear quadratic regulator (LQR) problem. The analytical solution of fractional optimal control near the origin and infinity are derived. It is shown that the optimal control to the linear fractional system can be computed through the corresponding fractional Euler-Lagrange equations.
Yan Li, YangQuan Chen
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