 Design of a self-tuning double EWMA controller for MIMO processesMing-Shan Lu and Shi Jer Wang International Journal of Industrial and Systems Engineering, 2015, vol. 21, issue 4, 438-457 Abstract: The design of time-varying multivariate discount factors for the double EWMA controller is essential for ensuring the consistency of output qualities. In this research, a self-tuning double EWMA controller for MIMO processes is proposed. First, the process estimator is used to obtain the online process parameters at each run based on the recursive least square method. Then, based on the estimated process model, the double EWMA controller is developed to generate the control inputs for compensating the variations of the process at each run. A genetic algorithm searches for the approximately optimal discount factors within the stable region at each run and the objective is to minimise the cost of the outputs deviating from targets and the adjustment amounts of the control inputs between each run. The obtained discount factors are automatically adjusted to adapt to the process variations and disturbances and to maintain the process running at controlled conditions. Keywords: double EWMA control; exponentially weighted moving average; controller design; self-tuning control; discount factors; genetic algorithms; MIMO processes; recursive least squares; parameter estimation; process variations. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:21:y:2015:i:4:p:438-457 Access Statistics for this article More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd |
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