A MULTILEVEL RESOURCE-SAVING BLAST FURNACE PROCESS CONTROL

A multilevel resource-saving blast furnace process control is considered. The resource-saving control is provided for operating, adaptation, technical and economic control in the automated systems of blast-furnace processes. It is proposed to form optimal operation modes of blast furnace heating, metal charge structures, natural gas and oxygen consumption. Decisions are made using Kohonen neural networks taking into account current and planned parameters of coke quality, iron ore, raw materials and blast. At the level of operating control, the work suggests a model predictive control to improve the resource conservation indicators. The method is based on decomposition of the general problem of the process dynamics identification on particular problems: dynamic synchronization and identification of process transfer functions. At the level of adaptive control, optimal operating modes of blast furnaces are expedient to be developed with respect to blast furnace heating, structure of metal charge, natural gas and oxygen rate considering the current and planned parameters of coke, blasting. The blast furnace operating modes are suggested to be determined based on Kohonen neural networks. In evaluating the efficiency of introducing the model predictive control, the existing actual statistics of scatter of BF mode parameters should be based upon. The fact is that the introduction of model predictive control assumes no radical change of the BF melt technology. Like in all the control systems, the BF process is considered as the set control object with all its characteristics. Changing process settings, raw material content does not introduce any cardinal variation in the scatter of process characteristics. However, in this case a transient process occurs which is necessary for the control system to identify the changing conditions. The transient process is inherent to all the control systems and the blast furnace process is not an exclusion. As a result of transient process, the control system is set to the optimal mode.

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Application of data reconciliation and gross error detection techniques to enhance reliability and consistency of the blast furnace process data

Asia-Pacific Journal of Chemical Engineering ◽

10.1002/apj.2628 ◽

2021 ◽

Author(s):

Sujan Hazra ◽

Prakash Abhale ◽

Samik Nag ◽

Sam Mathew ◽

Shankar Narasimhan

Keyword(s):

Blast Furnace ◽

Error Detection ◽

Data Reconciliation ◽

Blast Furnace Process ◽

Process Data ◽

Gross Error Detection ◽

Furnace Process ◽

Detection Techniques ◽

Gross Error

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State space stability analysis of unconstrained decentralized model predictive control systems

2006 American Control Conference ◽

10.1109/acc.2006.1655347 ◽

2006 ◽

Cited By ~ 3

Author(s):

M. Vaccarini ◽

S. Longhi ◽

R. Katebi

Keyword(s):

Stability Analysis ◽

Model Predictive Control ◽

State Space ◽

Control Systems ◽

Predictive Control ◽

Decentralized Model ◽

Decentralized Model Predictive Control

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Direct Longitudinal Force Feedback for High-Performance Vehicle Dynamics Control Systems

10.1115/detc2021-69432 ◽

2021 ◽

Author(s):

Giorgio Riva ◽

Luca Mozzarelli ◽

Matteo Corno ◽

Simone Formentin ◽

Sergio M. Savaresi

Keyword(s):

Model Predictive Control ◽

Control Systems ◽

Predictive Control ◽

Vehicle Dynamics ◽

High Performance ◽

Force Feedback ◽

Longitudinal Force ◽

Spiral Path ◽

Comparable Performance ◽

Vehicle Dynamics Control

Abstract State of the art vehicle dynamics control systems do not exploit tire road forces information, even though the vehicle behaviour is ultimately determined by the tire road interaction. Recent technological improvements allow to accurately measure and estimate these variables, making it possible to introduce such knowledge inside a control system. In this paper, a vehicle dynamics control architecture based on a direct longitudinal tire force feedback is proposed. The scheme is made by a nested architecture composed by an outer Model Predictive Control algorithm, written in spatial coordinates, and an inner longitudinal force feedback controller. The latter is composed by four classical Proportional-Integral controllers in anti-windup configuration, endowed with a suitably designed gain switching logic to cope with possible unfeasible references provided by the outer loop, avoiding instability. The proposed scheme is tested in simulation in a challenging scenario where the tracking of a spiral path on a slippery surface and the timing performance are handled simultaneously by the controller. The performance is compared with that of an inner slip-based controller, sharing the same outer Model Predictive Control loop. The results show comparable performance in presence of unfeasible force references, while higher robustness is achieved with respect to friction curve uncertainties.

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