Advanced hybrid fuzzy-neural controller for industrial wastewater treatment

摘要: Many uncertain factors affect the operation of wastewater treatment plants. These include physical and chemical properties streams as well degradation mechanisms exhibited by biological processes. Because rising concerns about environmental economic impacts, improved process control algorithms, using artificial intelligence technologies, have received wide attention. Recent advances in engineering suggest that hybrid strategies, integrating some ideas paradigms existing different soft computing techniques such fuzzy logic, genetic neural networks, may provide effluent quality. The methodology proposed this study employs a three-stage analysis integrates three approaches for generating representative state function, searching set multiobjective autotuning rule base used controlling plant. case study, an industrial plant Taiwan example, demonstrates applicability approach. findings from research genetic-algorithm–based fuzzy-neural controller can produce better performance than does simple logic controller, terms both objectives. This be extended to many other types processes, well, making only minor modifications.