Koçal, Osman Hilmi2022-04-202022-04-202012-05Hatun, 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), 435-450.0890-63271099-1115https://doi.org/10.1002/acs.1296https://onlinelibrary.wiley.com/doi/10.1002/acs.1296http://hdl.handle.net/11452/25907A 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.eninfo:eu-repo/semantics/closedAccessAutomation & control systemsEngineeringGauss-seidel algorithmSelf-tuning controlGeneralized minimum variance controlLyapunov stabilityAlgorithmsComputer simulationDigital control systemsDiscrete time control systemsController parameterDiscrete time systemForgetting factorsGauss Seidel iterationGauss-SeidelLyapunov stability theoryMinimum phaseNon-minimum phaseNon-minimum phase systemsRecursive algorithmsRecursive least square (rls)Self tuning controlsSelf-tuning controllersTime varying parameterParameter estimationSquares parameter-estimationIterative solutionsIdentificationArticle0003039783000052-s2.0-84861191596435450265Automation & control systemsEngineering, electrical & electronicStochastic Gradient; Recursive Identification; Autoregressive Moving Average