Abstract
The paper proposes a methodology to online self-evolve direct fuzzy logic controllers (FLCs), to deal with unknown and time-varying dynamics. The proposed methodology self-designs the controller, where fuzzy control rules can be added or removed considering a predefined criterion. The proposed methodology aims to reach a control structure easily interpretable by human operators. The FLC is defined by univariate fuzzy control rules, where each input variable is represented by a set of fuzzy control rules, improving the interpretability ability of the learned controller. The proposed self-evolving methodology, when the process is under control (online stage), adds fuzzy control rules on the current FLC using a criterion based on the incremental estimated control error obtained using the system’s inverse function and deletes fuzzy control rules using a criterion that defines “less active” and “less informative” control rules. From the results on a nonlinear continuously stirred tank reactor (CSTR) plant, the proposed methodology shows the capability to online self-design the FLC by adding and removing fuzzy control rules in order to successfully control the CSTR plant.
Highlights
The globalization of markets, environmental legislation restrictions, the necessity of having an efficient management of energy and sustainable resources, zero defect trends, customer pressure to reduce costs, personalized products, low product lifetime, and several other facts have resulted in a significant increase in industrial process complexity
The main contributions of the proposed self-evolving design methodology for direct fuzzy logic controllers (FLCs) are: the evolving of a control structure composed of univariate control rules, which together with the defined evolving mechanisms, makes the controller better interpretable by human operators, and having a light control structure; the criteria to add control rules are defined in order to reduce the sensitivity to noise/outliers; to delete fuzzy control rules, two criteria to delete
Since in this paper it is done the assumption that there is no knowledge about the dynamics of the process under control, in the offline design, the FLC is designed using the range values of the process’
Summary
The globalization of markets, environmental legislation restrictions, the necessity of having an efficient management of energy and sustainable resources, zero defect trends, customer pressure to reduce costs, personalized products, low product lifetime, and several other facts have resulted in a significant increase in industrial process complexity. The main contributions of the proposed self-evolving design methodology for direct FLCs are: the evolving of a control structure composed of univariate control rules, which together with the defined evolving mechanisms, makes the controller better interpretable by human operators, and having a light control structure (small number of membership functions and control rules); the criteria to add control rules are defined in order to reduce the sensitivity to noise/outliers; to delete fuzzy control rules, two criteria to delete “less active” or “less informative” rules are presented; and the threshold for the criteria to add or remove control rules are intuitively defined (by the percentage of the variables range and e ∈ [0, 1]).
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