Recursive Gauss-Seidel algorithm for direct self-tuning control
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Date
2012-05
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Publisher
Wiley
Abstract
A recursive algorithm based on the use of GaussSeidel iterations is introduced to adjust the parameters of a self-tuning controller for minimum phase and a class of nonminimum phase discrete-time systems. The proposed algorithm is called the Recursive GaussSeidel (RGS) algorithm and is used to update the controller parameters directly. The use of the RGS algorithm with a generalized minimum variance control law is also given for nonminimum phase systems, and a forgetting factor is used to track the time-varying parameters. Furthermore, the overall stability of the closed-loop system is proven by using the Lyapunov stability theory. Using computer simulations, the performance of the RGS algorithm is examined and compared with the widely used recursive least squares algorithm.
Description
Keywords
Automation & control systems, Engineering, Gauss-seidel algorithm, Self-tuning control, Generalized minimum variance control, Lyapunov stability, Algorithms, Computer simulation, Digital control systems, Discrete time control systems, Controller parameter, Discrete time system, Forgetting factors, Gauss Seidel iteration, Gauss-Seidel, Lyapunov stability theory, Minimum phase, Non-minimum phase, Non-minimum phase systems, Recursive algorithms, Recursive least square (rls), Self tuning controls, Self-tuning controllers, Time varying parameter, Parameter estimation, Squares parameter-estimation, Iterative solutions, Identification
Citation
Hatun, M. ve Koçal, O. H. (2012). "Recursive Gauss-Seidel algorithm for direct self-tuning control". International Journal of Adaptive Control and Signal Processing, 26(5), 435-450.