A design algorithm using external perturbation to improve Iterative Feedback Tuning convergence
2011 (English)In: Automatica, ISSN 0005-1098, Vol. 47, no 12, 2665-2670 p.Article in journal (Refereed) Published
Iterative Feedback Tuning constitutes an attractive control loop tuning method for processes in the absence of process insight. It is a purely data driven approach for optimization of the loop performance. The standard formulation ensures an unbiased estimate of the loop performance cost function gradient, which is used in a search algorithm for minimizing the performance cost. A slow rate of convergence of the tuning method is often experienced when tuning for disturbance rejection. This is due to a poor signal to noise ratio in the process data. A method is proposed for increasing the data information content by introducing an optimal perturbation signal in the tuning algorithm. The theoretical analysis is supported by a simulation example where the proposed method is compared to an existing method for acceleration of the convergence by use of optimal prefilters.
Place, publisher, year, edition, pages
2011. Vol. 47, no 12, 2665-2670 p.
Controller tuning, Direct tuning, Iterative Feedback Tuning, Iterative schemes, Control loop, Data informations, Data-driven approach, External perturbations, Loop performance, Optimal perturbation, Performance costs, Prefilters, Process data, Rate of convergence, Search Algorithms, Simulation example, Tuning algorithm, Tuning method, Unbiased estimates, Algorithms, Approximation theory, Cost benefit analysis, Disturbance rejection, Optimization, Signal to noise ratio, Time varying networks, Convergence of numerical methods
Research subject SRA - ICT
IdentifiersURN: urn:nbn:se:kth:diva-60498DOI: 10.1016/j.automatica.2011.05.029ISI: 000298071000013ScopusID: 2-s2.0-81155123058OAI: oai:DiVA.org:kth-60498DiVA: diva2:478551
QC 201201172012-01-162012-01-132012-01-23Bibliographically approved