A Dynamic-Attention-Based Heuristic Fuzzy Expert System for the Tuning of Microwave Cavity Filters

The tuning of microwave cavity filters (MCFs) is mostly conducted by experienced operators, and thus, is time and resource intensive. The automatic tuning method has received lots of research attention. However, the experience of tuning experts is not described systematically, and the existing methods are not adequate for MCFs with individual differences. Considering that fuzzy expert systems are superior in flexibility and interpretability, a dynamic-attention-based heuristic fuzzy expert system is proposed in this article to achieve automatic tuning with high applicability, accuracy, and efficiency. First, the dynamic tuning process is divided into several stages, and the evaluation function of filtering performance is designed for each stage. Second, an improved expert system with dynamic attention is constructed to facilitate the comprehensive evaluation of filtering performance and to balance tuning efficiency and accuracy. Third, a heuristic fuzzy logic system is presented to obtain appropriate tuning values, with low design complexity of fuzzy rules and high utilization of tuning process information. Finally, the effectiveness, applicability, and practicality of the proposed method are demonstrated by both simulations and experiments.