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1. 发明申请

WO2013119665A1 APPARATUS AND METHODS FOR NON-INVASIVE CLOSED LOOP STEP TESTING USING A TUNABLE TRADE-OFF FACTOR 审中-公开
标题翻译：装置和方法使用无阻碍贸易关闭因子进行非入门闭合环路测试
公开(公告)号：WO2013119665A1
公开(公告)日：2013-08-15
申请号：PCT/US2013/024932
申请日：2013-02-06
申请人： ASPEN TECHNOLOGY, INC.
发明人： ZHENG, Qingsheng, Quinn , HARMSE, Magiel, J.
IPC分类号： G05B13/04
CPC分类号： G05B13/022 , G05B13/048
摘要： An integrated multivariable predictive controller (MPC) and tester is disclosed. The invention system provides optimal control and step testing of a multivariable dynamic process using a small amplitude step for model identification purposes, without moving too far from optimal control targets. A tunable parameter specifies the trade-off between optimal process operation and minimum movement of process variables, establishing a middle ground between running a MPC on the Minimum Cost setting and the Minimum Move setting. Exploiting this middle ground, embodiments carry out low amplitude step testing near the optimal steady state solution, such that the data is suitable for modeling purposes. The new system decides when the MPC should run in optimization mode and when it can run in constrained step testing mode. The invention system determines when and how big the superimposed step testing signals can be, such that the temporary optimization give-away is constrained to an acceptable range.
摘要翻译：公开了一种综合多变量预测控制器（MPC）和测试仪。本发明系统提供了用于模型识别目的的小幅度步长的多变量动态过程的最佳控制和步长测试，而不会偏离最佳控制目标。可调参数指定最佳过程操作与过程变量的最小移动之间的权衡，建立在最小成本设置上运行MPC和最小移动设置之间的中间位置。利用这个中间点，实施例在最优稳态解决方案附近进行低幅度步长测试，使得数据适合建模目的。新系统决定MPC何时运行在优化模式下，以及何时可以在受限步骤测试模式下运行。本发明系统确定叠加的步骤测试信号的何时以及有多大，使得临时优化赠送被限制在可接受的范围内。

2. 发明申请

WO2020091942A1 APPARATUS AND METHODS FOR NON-INVASIVE CLOSED LOOP STEP TESTING WITH CONTROLLABLE OPTIMIZATION RELAXATION 审中-公开
公开(公告)号：WO2020091942A1
公开(公告)日：2020-05-07
申请号：PCT/US2019/054465
申请日：2019-10-03
申请人： ASPEN TECHNOLOGY, INC.
发明人： ZHENG, Qingsheng, Quinn
IPC分类号： G05B17/02 , G05B13/04
摘要： A controller has improved closed-loop step testing of a dynamic process of an industrial processing plant. The controller performs economic optimization relaxation on process variables, such that operating range of the variables (MVs and CVs) during the testing are not skewed by variations in optimization cost factors. The controller employs computer-implemented methods and systems that receive a user-defined giveaway tolerance representing an allowable range between a current process variable value and a target process variable value. In response to the variables not meeting the giveaway tolerance, the methods and systems adjust the MFC controller configuration to drive the variables inside the tolerance, while relaxing optimization of the variables already meeting the giveaway tolerance. Using the adjusted configuration, the methods and systems calculate a new set of targets and generate a dynamic move plan from the new target. The methods and systems add perturbation signals for the testing to the move plan in accordance with the adjusted configuration.

3. 发明申请

WO2015167741A1 IMPROVED ONLINE CONTROL CALCULATION FOR MODELS CONTAINING NEAR COLINEARITY AND UNCERTAINTY 审中-公开
标题翻译：改进了包含近似和不确定性模型的在线控制计算
公开(公告)号：WO2015167741A1
公开(公告)日：2015-11-05
申请号：PCT/US2015/023904
申请日：2015-04-01
申请人： ASPEN TECHNOLOGY, INC.
发明人： KEENAN, Michael, R. , ZHENG, Qingsheng, Quinn , HARMSE, Magiel, J.
IPC分类号： G05B17/02
CPC分类号： G05B13/048 , G05B17/02
摘要： A method, apparatus, and computer program product for increasing closed-loop stability in a MPC controller controlling a process where there are significant uncertainties in the model used by the controller. This invention focuses on the improvement of the robustness of the steady-state target calculation. This is achieved through the use of a user defined robustness factor, which is then used to calculate an economic objective function giveaway tolerance and controlled variable constraint violation tolerance. The calculation engine uses these tolerances to find a solution that minimize the target changes between control cycles and prevent weak direction moves caused by near collinearity in the model. If the controller continues to exhibit large variations in the process, it can slow down the manipulated variable movement to stabilize the process.
摘要翻译：一种用于增加MPC控制器中的闭环稳定性的方法，装置和计算机程序产品，其控制在控制器使用的模型中存在显着不确定性的过程。本发明着重于提高稳态目标计算的鲁棒性。这是通过使用用户定义的鲁棒性因子实现的，然后用于计算经济目标函数赠品容限和受控变量约束违规容限。计算引擎使用这些公差来找到最小化控制周期之间的目标变化的解决方案，并防止由模型中近似共线性引起的弱方向移动。如果控制器继续在过程中出现大的变化，则可以减慢操纵变量运动以稳定过程。

4. 发明申请

WO2021076760A1 SYSTEM AND METHODS FOR AUTOMATED MODEL DEVELOPMENT FROM PLANT HISTORICAL DATA FOR ADVANCED PROCESS CONTROL 审中-公开
公开(公告)号：WO2021076760A1
公开(公告)日：2021-04-22
申请号：PCT/US2020/055787
申请日：2020-10-15
申请人： ASPEN TECHNOLOGY, INC.
发明人： ZHAO, Hong , ZHENG, Qingsheng, Quinn , RIDLEY, Kerry, Clayton , LAO, Liangfeng , FANG, Yizhou
IPC分类号： G05B13/04
摘要： Systems and methods provide a new paradigm of Advanced Process Control that includes building and deploying APC seed models. Embodiments provide automated data cleansing and selection in model identification and adaption in multivariable process control (MPC) techniques. Rather than plant pre-testing onsite for building APC seed models, the embodiments help APC engineers to build APC seed models from existing plant historical data with self-learning automation and pattern recognition, AI techniques. Embodiments further provide "growing" and "calibrating" the APC seed models online with non-invasive closed loop step testing techniques. PID loops and associated SP, PV, and OPs are searched and identified. Only "informative moves" data is screened, identified, and selected among a long history of process variables for seed model development and MPC application. The seed models are efficiently developed while skipping the costly traditional pre-testing steps and minimizing the interferences to the subject production process.

5. 发明申请

WO2016176214A1 FORMULATING STEADY-STATE TARGETS USING PRIORITIZED OBJECTIVE FUNCTIONS 审中-公开
标题翻译：使用优先目标函数制定稳态目标
公开(公告)号：WO2016176214A1
公开(公告)日：2016-11-03
申请号：PCT/US2016/029379
申请日：2016-04-26
申请人： ASPEN TECHNOLOGY, INC.
发明人： ZHENG, Qingsheng, Quinn , KEENAN, Michael, R. , REIS, Lucas, L., G. , GHORPADE, Subhash , HARMSE, Magiel, J.
IPC分类号： G05B13/04 , G05B17/02
CPC分类号： G05B13/042 , G05B13/048 , G05B17/02
摘要： Computer system and methods for optimally controlling the behavior of an industrial process, in accordance with plant operating goals, without requiring a complicated trial and error process. The system and methods enable configuring optimization preference and optimization priority for key manipulated variables (MVs) of the industrial process. The system and methods translate the configured optimization preference and optimization priority for each key MV into prioritized economic objective functions. The system and methods calculate a set of normalized cost factors for use in a given prioritized economic functions based on a model gain matrix of manipulated variables and controlled variables of the industrial process. The system and methods automatically determine best achievable targets for the MVs by solving each prioritized economic objective functions in sequence of priority within the constraints of: (1) the determined CV best achievable steady-state targets, and (2) the determined MV best achievable steady-state targets from higher prioritized economic objective functions.
摘要翻译：根据工厂运行目标，最佳地控制工业过程的行为的计算机系统和方法，而不需要复杂的试错过程。该系统和方法能够为工业过程的关键操作变量（MV）配置优化偏好和优化优先级。系统和方法将每个关键MV的配置的优化优先级和优化优先级转化为优先的经济目标函数。系统和方法基于工业过程的操纵变量和受控变量的模型增益矩阵计算用于给定优先经济函数的一组归一化成本因子。系统和方法通过在以下限制内解决优先顺序的每个优先级经济目标函数来自动确定MV的最佳可实现目标：（1）确定的CV最佳可实现的稳态目标，以及（2）确定的最佳可实现的MV 较高优先经济目标函数的稳态目标。

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