摘要
为实现对非线性和时变系统的更精准建模和控制,适应系统动态变化和参数变化,应对系统变化和外部干扰,实现更可靠和安全的过程生产控制,提出一种新型模型预测控制策略。基于分数阶微积分运算的扩展非最小状态空间模型预测控制(ENMSSFMPC)算法,状态空间模型包含状态变量和输出跟踪误差,通过分数阶定义将系统模型离散化,利用ENMSSFMPC对比例—积分—微分(PID)控制器进行参数滚动优化,获得实时最优控制参数。原油稳定加热炉模型仿真结果表明,该控制策略优于传统的模型预测控制、非最小状态空间模型预测控制和分数阶模型预测控制。
In order to achieve more accurate modeling and control of nonlinear and time-varying systems,adapt to system dynamic changes and parameter changes,cope with system changes and external interference,and achieve more reliable and safe process production control,a new model predictive control strategy is proposed.An extended non-minimum state space model predictive control(ENMSSFMPC)algorithm based on fractional calculus operations is proposed,in which the state space model contains state variables and output tracking errors.The system model is discretized by fractional order definition,and the proportional-integral-derivative(PID)controller is optimized by ENMSSFMPC to obtain real-time optimal control parameters,and the simulation test is carried out on the crude oil stable heating furnace model.The simulation results verify that the control strategy is superior to the traditional model predictive control,non-minimum state-space model predictive control and fractional order model predictive control.
作者
王思宇
王炳淇
邵克勇
WANG Siyu;WANG Bingqi;SHAO Keyong(Instrument Telecommunication Room,Daqing Oilfield Design Institute,Daqing,Heilongjiang 163712,China;School of Electrical and Information Engineering,Northeast Petroleum University,Daqing,Heilongjiang 163318,China)
出处
《东北石油大学学报》
CAS
北大核心
2023年第3期89-97,I0007,I0008,共11页
Journal of Northeast Petroleum University
基金
黑龙江省高校基本科研项目(2022TSTD-04)。
