Abstract: During the operation of the industrial process, the optimal control objective is to control the technique indices that represent the quality, the efficiency, and the consumption of the product processing into its targeted ranges. However, due to the difficulty of measuring the technique indices on-line of the complex industrial process, the dynamics between the techniques and the control loops with complex natures, such as strong nonlinearity, heavy coupling and difficulty of description by the accurate model, and its dynamics varying with the process conditions, such a control objective by far is difficult to achieve by the existing control methods, thus the only way of manual control is adopted. However, the manual control cannot adjust the setting point according to the conditions of the operation process timely and exactly. Therefore, it is difficult to control the technique indices into its desired ranges and even cause fault work-condition. In this paper, A hybrid intelligent control method for process optimal operation is proposed, which controls the technique indices into the desired ranges by on-line adjusting the set-points of the control loops according to the operation condition, enabling the control system totrack the adjusted set-points. The proposed method is comprised of a control loop presetting model, feedforward and feedback compensators, a prediction model of the technique indices and a fault work-condition diagnosis unit plus a fault-tolerancecontroller. An application case study is given to illustrate the method being applied to a roasting process with 22 shaft furnaces in one ore concentration plant, and the application results have proven the effectiveness of the proposed method.