This article proposes a general formulation for temporal parallelization of dynamic programming optimal control problems. We derive the elements and associative operators to be able use parallel scans solve these problems with logarithmic time complexity rather than linear complexity. apply this methodology finite state spaces, quadratic tracking problems, class nonlinear The computational bene...

<p style='text-indent:20px;'>In this work, we have proposed a new approach for solving the linear-quadratic optimal control problem, where quality criterion is quadratic function, which can be convex or non-convex. In approach, transform continuous problem into optimization using Cauchy discretization technique, then solve it with active-set method. order to study efficiency and accuracy ...

In this paper, a robust and optimal control method is proposed for the attitude control problem of multirotors. The designed controller consists of an optimal controller and a robust compensator. The optimal controller is designed based on the linear quadratic regulation control method for the desired tracking of the nominal linear system, whereas the robust compensator is introduced to restrai...

Design of power system stabilizer using Linear Quadratic Regulator (LQR) technique. Designs that ignore noise in a plant are likely to fail when implemented in actual conditions. Presence of the noise, which results in LQR output oscillating with very small magnitude. This type of unwanted noisy output is eliminated using Linear Quadratic Gaussian (LQG) Regulator. This paper presents techniques...

in this paper, the consequences of well-known characteristics of near-fault ground motions, forward directivity and fling step, on the seismic response control is investigated. an integrated fuzzy rule-based control strategy for building structures incorporated with semi active friction damping system with amplifying braces (fdsab) is developed. the membership functions and fuzzy rules of fuzzy...

Abstract: Both the linear moving horizon estimator and controller may be solved by solving a linear quadratic optimal control problem. A primal active set, a dual active set, and an interior point algorithm for solution of the linear quadratic optimal control problem are presented. The major computational effort in all these algorithms reduces to solution of certain unconstrained linear quadrat...

We consider the exploration-exploitation tradeoff in linear quadratic (LQ) control problems, where the state dynamics is linear and the cost function is quadratic in states and controls. We analyze the regret of Thompson sampling (TS) (a.k.a. posterior-sampling for reinforcement learning) in the frequentist setting, i.e., when the parameters characterizing the LQ dynamics are fixed. Despite the...