Convergence Analysis using non-squares estimators to approximate the solution of HJB-Riccati equation for the design DLQR via HDP

Author

Queiroz, Jonathan A. ; Rego, Patricia H. M. ; Neto, Joao V. F. ; Da Silva, Cristiane ; Santana, Ewaldo ; Kardec Barros, Allan

Author_Institution

Embedded Syst. & Intell. Control Lab., Fed. Univ. of Maranhao, Sao Luis, Brazil

fYear

2014

Firstpage

63

Lastpage

68

Abstract

The proposed methodology is based on development of online algorithms for approximate solutions of the Hamilton-Jacobi-Bellman (HJB) equation through a family of non-squares approximators for critic adaptive solution of the Discrete Algebraic Riccati Equation (DARE), associated with the problem of Discrete Linear Quadratic Regulator (DLQR). The proposed method is evaluated in a multivariable dynamic system of 4th order with two inputs and it is compared with standard recursive least square algorithm.

Keywords

Riccati equations; control system synthesis; convergence; discrete systems; dynamic programming; least squares approximations; linear quadratic control; multivariable control systems; recursive estimation; DARE; DLQR design; HDP; HJB; Hamilton-Jacobi-Bellman equation; convergence analysis; discrete algebraic Riccati equation; discrete linear quadratic regulator; heuristic dynamic programming; multivariable dynamic system; nonsquares approximation; recursive least square algorithm; Algorithm design and analysis; Approximation algorithms; Convergence; Dynamic programming; Equations; Mathematical model; Vectors; Discrete Algebraic Riccati Equation; Discrete Linear Quadratic Regulator; Hamilton-Jacobi-Bellman Equation; Heuristic Dynamic Programming; Non-squares Approximators; Recursive Least-Squares;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on

Print_ISBN

978-1-4799-4923-6

Type

conf

DOI

10.1109/UKSim.2014.107

Filename

7046040