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DCS provides a powerful hardware and software platform for advanced control for its popularity and improvement. To take full advantage of DCS system, this paper proposes an adaptive fuzzy-neural controller considering of the characteristics of the complex industrial processes. It focuses on the hybrid learning algorithm of adaptive fuzzy and neural network. It uses the interface and programming language of DCS to study the advanced control, and comprises of artificial intelligence, expert system, and fuzzy neural network control. The effectiveness of the proposed scheme is illustrated through simulation and the practical usage of complex in resistance furnace temperature control system. It is proven its feasibility and achieves satisfactory control effect.