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With ever increased needs for an improved product quality, production efficiency, and cost in today's globalized world market, advanced process control should not only realize the accuracy of each control loops, but also has the ability to achieve an optimization control of global production indices that are closely related to the improved product quality, enhanced production efficiency and reduced consumption. The optimal control of the global production indices requires an optimal combination of the production indices, technical indices and the operation of each control loops. In this talk, a hybrid intelligent control strategy is proposed for process industries. This new strategy consists of three control layers, namely the intelligent optimization of the global production indices, the intelligent optimal control of the technical indices and the intelligent process control. The intelligent optimization of the global production indices is composed of the setting model of the technical indices, the predictor of the global production indices, the feedback and prediction analysis adjustment models. The intelligent optimal control of the technique indices consists of the set-points model of control loops, the prediction of technical indices, and the feedback and feed-forward regulators. The intelligent process control is then composed of normal decoupled PID controllers, decoupled nonlinear PID controllers with a neural network feed-forward compensator for un-modeled dynamics and a switching mechanism. Such a control structure can automatically transfer the global production indices into a required number of set-points for each control loops.