多层结构预测控制系统经济性能评估与优化设计
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摘要
随着模型预测控制技术在石油、化工、造纸、制药等流程工业的迅速发展和广泛应用,企业的安全生产得到了保障,经济效益有了明显提高。由于预测控制的实施需要增加企业投资成本,能否在项目实施前给出详细准确的投运成本和经济收益分析,是企业关心的一个重要问题。根据工程实施经验,预测控制系统在投运初期能够达到预期的控制性能目标,然而,随着时间的推移,原料供给、产品规格、生产环境、设备性能、操作条件等都发生了变化,预测控制器逐渐偏离预先设定的操作状态,导致控制性能下降,无法达到预期收益。因此,预测控制系统的经济性能评估具有十分重要的意义。目前应用最为广泛的性能评估策略基于最小方差控制(Minimum Variance Control, MVC)基准。然而,由于MVC基准只涉及到过程输出的方差信息,并没有考虑执行器的约束和可操作性,因而在工业应用中只能作为一种理想化的操作指导而通常无法实现。针对这一问题,本论文基于线性二次型高斯(Linear Quadratic Gaussian, LQG)基准进行多层结构预测控制系统经济性能评估与优化的研究,在充分考虑了执行器约束的情况下给出实际可行的最优控制策略。本论文具体研究内容如下：
1.针对流程工业中的多变量预测控制器,采用多变量LQG经济性能稳态优化与MPC动态控制结合的双层优化控制结构,通过求解多变量LQG性能基准,确定了多变量控制方差与输出方差非线性约束关系的多维Pareto曲面,从而对控制过程进行经济性能评估和稳态优化求解,给出与经济效益直接相关的多变量MPC最优设定值和最优卡边控制退避值,进一步指导MPC控制器设计以实现最优控制性能和最大化经济效益。
2.针对传统LQG最优性能基准点上部密集,下部稀疏的不均衡分布导致的拟合效果偏差和计算量过大的问题,提出了一种均匀分布LQG性能评估策略。分别采用数值寻优算法、递归寻优算法和解析求解算法三种策略求解LQG最优离散点集,并对该点集进行拟合,从而提高了LQG性能曲线的拟合精度,降低了计算量。对于多变量控制系统,采用LQG性能基准对变量之间的制约关系进行灵敏度分析,能够指导控制及评估变量的选取,提高调节效率和简化评估流程。
3.针对工业过程中由于原料批次变化、生产环境影响、牌号切换、操作员调整等因素导致的多模型工况,根据多模型过程产生的原因将其区分为扰动多模型和过程多模型分别展开讨论,介绍了MVC评估基准对于多模型问题的解决策略,并分别对扰动多模型和过程多模型工况采用LQG基准进行性能评估和稳态优化设计。
4.针对多层结构预测控制系统中各层之间变量处理相对独立而导致的约束不一致、最优设定值无法执行、控制性能降低的问题,分别对LQGO—PFC—PFC、LQGO—PFC—PID、LQGO—QMPC—PID三种典型的串级控制回路和传导控制回路进行分析,在多层结构协调运算过程中采用回退计算策略将下层控制器约束传递至上层,并对约束传递过程中的单调性做了证明,从而保证各层之间约束的一致性,提高控制效果。通过液位控制系统的设计验证了该方法的有效性。
5.针对目前经济性能评估大多基于稳态过程而未考虑动态特性的问题,采用LQG稳态优化与MPC动态控制相结合的双层MPC优化控制结构,将过程关键变量作为上下层之间的关联,从而保证了上层最优经济性能下的设定值切实可行。采用提出的多变量LQG性能基准和均匀分布LQG性能基准分别对国内某大型石化企业延迟焦化加热炉出口氧含量控制回路和加热炉出口温度控制回路进行了经济性能评估和优化设计,给出了加热炉控制系统的经济性能提升空间,并指导MPC控制器设计。
As the most typical Advanced Process Control (APC) technology, Model Predictive Control (MPC) can enhance enterprises economic benefits effectively and has found wide applications in process industry, including petroleum industry, chemical industry, papermaking, pharmaceutical industry, etc. Since the implementation of MPC control system needs additional investment which generally involves a large cost, the benefit and cost ratio is one of the most important factors to be considerated by enterprises. Generally, most MPC controllers operate reasonably well at the early stage. However, their performance may deteriorate after a certain period due to the variation of operating conditions and producion environments. In the worst case, the process might even become uncontrollable and the MPC controllers have to be switched off. resulting in a large waste of investment and loss of economic benefits. Therefore, the economic performance assessment of MPC is important and has attract a lot of interest by academia and industry. Currently, the most common assessment method is the Minimum Variance Control (MVC) benchmark. By comparing the actual variance of the process with the MVC benchmark, the performance improvement potential is provided. However, MVC only deals with process output variance without considering the actuator constraints, so this benchmark is usually deemed as an ideal performance assessing guideline but seldom-implemented in industrial applications. Instead, to implement the economic performance assessment and optimization for multi-layer MPC structure, the LQG benchmark which considers both the manipulated variables variance and the controlled variables variance with a quadratic dynamic index is adopted in this thesis. The research topics include:
1.The economic performance assessment is considered for multi-variable controllers in petrochemical processes, an integrated two-layer structure of LQG economic performance steady state optimization and MPC dynamic optimization is given, the relationship between the controlled variables variance and the manipulated variables variance is calculated and accordingly its optimal Pareto surface function is obtained by regression method, and a pragmatic economic performance assessment and optimization strategy for multi-variable process is introduced. Hence the optimal setpoints for MPC and optimial back-off values can be determined.
2. An equigrid LQG benchmark is introduced to improve the traditional LQG benchmark which was determined from an asymmetrically distributed discrete points set with unnecessary computation and unsatisfied regression effect. Three approaches consisting of numerical equigrid algorithm, recursive equigrid algorithm and analytical equigrid algorithm for calculating the equigrid LQG benchmark are introduced based on the ARMAX model processes, hence the regression effect is improved and the computing cost is reduced. Based on the LQG benchmark, the sensitivity analysis strategy for each pair of manipulated variable and controlled variable is introduced.
3. The LQG benchmark for multi-model processes is introduced to deal with the multiple operation situations caused by materials varying, environment fluctuation, product switching, operator change and so on. According to different causations, the multi-model situations include multiple disturbance models and multiple process models. Based on the analysis of MVC benchmark, the LQG performance assessment and optimization for multi-model processes are introduced.
4. To avoid the problem that the calculated optimization setpoints from upper layer are not available in lower-layer because of actuator physical limits, which will lead to control performance deterioration, and to ensure the constraints consistency in multi-layer MPC control and optimization structure, the back-calculation from basic control layer to upper layer is introduced, the consistency of constraints in different layers is proved. The constraints consistency of three typical cascade control loop or transparent control loop of LQGO—PFC—PFC, LQGO-PFC-PID, LQGO-QMPC—PID are analyzed. Based on the above consideration, a cascade level control system is designed and the control results show the effectiveness of the proposed approach.
5. The integrated structure of LQG based steady state optimization and MPC dynamic control is used for economic performance assessment, to replace the current strategies for which the steady state optimization and dynamic control are separated. The crucial variables are selected as the connections between the two layers, to ensure the calculated optimal setpoints from upper layer are always practical in lower layer. The economic performance assessment and optimization for the outlet Oxygen content control loop and the outlet temperature control loop of delayed coking furnace in a large petrochemical enterprise of China are implemented, hence the profit margin in delayed coking furnace is analyzed and the parameters designing rules of MPC controller are given.
1.针对流程工业中的多变量预测控制器,采用多变量LQG经济性能稳态优化与MPC动态控制结合的双层优化控制结构,通过求解多变量LQG性能基准,确定了多变量控制方差与输出方差非线性约束关系的多维Pareto曲面,从而对控制过程进行经济性能评估和稳态优化求解,给出与经济效益直接相关的多变量MPC最优设定值和最优卡边控制退避值,进一步指导MPC控制器设计以实现最优控制性能和最大化经济效益。
2.针对传统LQG最优性能基准点上部密集,下部稀疏的不均衡分布导致的拟合效果偏差和计算量过大的问题,提出了一种均匀分布LQG性能评估策略。分别采用数值寻优算法、递归寻优算法和解析求解算法三种策略求解LQG最优离散点集,并对该点集进行拟合,从而提高了LQG性能曲线的拟合精度,降低了计算量。对于多变量控制系统,采用LQG性能基准对变量之间的制约关系进行灵敏度分析,能够指导控制及评估变量的选取,提高调节效率和简化评估流程。
3.针对工业过程中由于原料批次变化、生产环境影响、牌号切换、操作员调整等因素导致的多模型工况,根据多模型过程产生的原因将其区分为扰动多模型和过程多模型分别展开讨论,介绍了MVC评估基准对于多模型问题的解决策略,并分别对扰动多模型和过程多模型工况采用LQG基准进行性能评估和稳态优化设计。
4.针对多层结构预测控制系统中各层之间变量处理相对独立而导致的约束不一致、最优设定值无法执行、控制性能降低的问题,分别对LQGO—PFC—PFC、LQGO—PFC—PID、LQGO—QMPC—PID三种典型的串级控制回路和传导控制回路进行分析,在多层结构协调运算过程中采用回退计算策略将下层控制器约束传递至上层,并对约束传递过程中的单调性做了证明,从而保证各层之间约束的一致性,提高控制效果。通过液位控制系统的设计验证了该方法的有效性。
5.针对目前经济性能评估大多基于稳态过程而未考虑动态特性的问题,采用LQG稳态优化与MPC动态控制相结合的双层MPC优化控制结构,将过程关键变量作为上下层之间的关联,从而保证了上层最优经济性能下的设定值切实可行。采用提出的多变量LQG性能基准和均匀分布LQG性能基准分别对国内某大型石化企业延迟焦化加热炉出口氧含量控制回路和加热炉出口温度控制回路进行了经济性能评估和优化设计,给出了加热炉控制系统的经济性能提升空间,并指导MPC控制器设计。
As the most typical Advanced Process Control (APC) technology, Model Predictive Control (MPC) can enhance enterprises economic benefits effectively and has found wide applications in process industry, including petroleum industry, chemical industry, papermaking, pharmaceutical industry, etc. Since the implementation of MPC control system needs additional investment which generally involves a large cost, the benefit and cost ratio is one of the most important factors to be considerated by enterprises. Generally, most MPC controllers operate reasonably well at the early stage. However, their performance may deteriorate after a certain period due to the variation of operating conditions and producion environments. In the worst case, the process might even become uncontrollable and the MPC controllers have to be switched off. resulting in a large waste of investment and loss of economic benefits. Therefore, the economic performance assessment of MPC is important and has attract a lot of interest by academia and industry. Currently, the most common assessment method is the Minimum Variance Control (MVC) benchmark. By comparing the actual variance of the process with the MVC benchmark, the performance improvement potential is provided. However, MVC only deals with process output variance without considering the actuator constraints, so this benchmark is usually deemed as an ideal performance assessing guideline but seldom-implemented in industrial applications. Instead, to implement the economic performance assessment and optimization for multi-layer MPC structure, the LQG benchmark which considers both the manipulated variables variance and the controlled variables variance with a quadratic dynamic index is adopted in this thesis. The research topics include:
1.The economic performance assessment is considered for multi-variable controllers in petrochemical processes, an integrated two-layer structure of LQG economic performance steady state optimization and MPC dynamic optimization is given, the relationship between the controlled variables variance and the manipulated variables variance is calculated and accordingly its optimal Pareto surface function is obtained by regression method, and a pragmatic economic performance assessment and optimization strategy for multi-variable process is introduced. Hence the optimal setpoints for MPC and optimial back-off values can be determined.
2. An equigrid LQG benchmark is introduced to improve the traditional LQG benchmark which was determined from an asymmetrically distributed discrete points set with unnecessary computation and unsatisfied regression effect. Three approaches consisting of numerical equigrid algorithm, recursive equigrid algorithm and analytical equigrid algorithm for calculating the equigrid LQG benchmark are introduced based on the ARMAX model processes, hence the regression effect is improved and the computing cost is reduced. Based on the LQG benchmark, the sensitivity analysis strategy for each pair of manipulated variable and controlled variable is introduced.
3. The LQG benchmark for multi-model processes is introduced to deal with the multiple operation situations caused by materials varying, environment fluctuation, product switching, operator change and so on. According to different causations, the multi-model situations include multiple disturbance models and multiple process models. Based on the analysis of MVC benchmark, the LQG performance assessment and optimization for multi-model processes are introduced.
4. To avoid the problem that the calculated optimization setpoints from upper layer are not available in lower-layer because of actuator physical limits, which will lead to control performance deterioration, and to ensure the constraints consistency in multi-layer MPC control and optimization structure, the back-calculation from basic control layer to upper layer is introduced, the consistency of constraints in different layers is proved. The constraints consistency of three typical cascade control loop or transparent control loop of LQGO—PFC—PFC, LQGO-PFC-PID, LQGO-QMPC—PID are analyzed. Based on the above consideration, a cascade level control system is designed and the control results show the effectiveness of the proposed approach.
5. The integrated structure of LQG based steady state optimization and MPC dynamic control is used for economic performance assessment, to replace the current strategies for which the steady state optimization and dynamic control are separated. The crucial variables are selected as the connections between the two layers, to ensure the calculated optimal setpoints from upper layer are always practical in lower layer. The economic performance assessment and optimization for the outlet Oxygen content control loop and the outlet temperature control loop of delayed coking furnace in a large petrochemical enterprise of China are implemented, hence the profit margin in delayed coking furnace is analyzed and the parameters designing rules of MPC controller are given.
引文
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