快速增量约束预测控制及在GLCC液位控制中的应用

针对气-液柱状旋流式(GLCC)多相流量计的液位控制问题,提出一种增量多变量模型预测控制(MPC)算法。采用控制增量状态空间模型和阶梯式控制策略,建立约束多变量MPC优化控制问题。为在线计算约束优化问题,引入坐标轮换法和黄金分割法,在线计算控制变量增量值,进而得到预测控制量。最后,以GLCC多相流量计的两输入单输出液位控制模型为例,仿真验证本文算法的有效性。

Fast incremental predictive control with constraints and its application to control of GLCC liquid-level

For liquid-level control problem of gas-liquid cylindrical cyclone(GLCC) multi-phase flow device,an incremental multi-variables model predictive control(MPC) algorithm was proposed.By using state-space models with incremental control and the stair-like strategy,constrained multi-variables MPC was formulated as an optimized control problem.In order to solve the constrained optimization problem,the methods of coordinate alternation and golden section were introduced to calculate online the value of incremental control variables.This led to predictive control actions.Finally,the liquid-level control model with double-inputs and single-output of the GLCC multi-phase flow device was used to illustrate the effectiveness of the algorithm obtained.