Fictitious Reference Iterative Tuning of Discrete-Time Model-Free Control for Tower Crane Systems
Raul-Cristian Roman, Radu-Emil Precup, E. Petriu, Mihai Muntyan
AI summary
70% confidenceA novel controller, FRIT-iPID, is proposed by combining FRIT and MFC algorithms to optimize iPID controller parameters using AVOA, validated on a tower crane system.
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Abstract
: The purpose of this paper is to propose a novel controller that is based on a combination of two data-driven algorithms, namely the Fictitious Reference Iterative Tuning (FRIT) algorithm and the Model-Free Adaptive Control (MFC) algorithm while considering a particular form of MFC, that is the intelligent proportional-integral-derivative (iPID) controller. The main advantage of this combination is that the FRIT algorithm optimally tunes the parameters of the iPID controller by solving an optimization problem based on a metaheuristic African Vultures Optimization Algorithm (AVOA). The novel controller, referred to as the FRIT-iPID controller, is validated experimentally on a three-degree-of-freedom tower crane system laboratory equipment in the context of controlling the cart position, the arm angular position and the payload position for this system.
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Identifiers
- Journal
- Studies in Informatics and Control
- Year
- 2023