Title :
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
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;
Conference_Titel :
Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on
Print_ISBN :
978-1-4799-4923-6
DOI :
10.1109/UKSim.2014.107
