复杂工业过程运行的混合智能优化控制方法

Hybrid Intelligent Optimal Control Method for Operation of Complex Industrial Processes

工业过程运行的优化控制的目标是将反应产品在加工过程中的质量、效率、消耗的工艺指标控制在目标值范围内.由于复杂工业过程的工艺指标难于在线测量且与控制回路输出之间的动态特性具有强非线性、强耦合、难以用精确模型描述、随生产边界条件变化而变化的综合复杂性,因此,难以采用已有优化控制方法,运行控制只能采用人工设定的控制方式.由于人工控制不能及时准确地随运行工况调整设定值,难以将工艺指标控制在目标值范围内,甚至造成故障工况.本文提出了根据运行工况实时调整控制回路设定值,通过控制系统跟踪调整后的设定值,将工艺指标控制在目标值范围内的过程优化运行的混合智能控制方法.该方法由控制回路预设定模型、前馈补偿与反馈补偿器、工艺指标预报模型、故障工况诊断和容错控制器组成.在某选矿厂22台竖炉组成的焙烧过程的应用案例,证明了所提出方法的有效性.

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.