Industry applications of multivariable control

In the face of environmental regulations, optimization of industrial processes becomes necessary. This doctoral thesis summarizes the results of three application-driven projects in automatic control that were aimed at process optimization in the steel industry. The objective of the projects was to apply advanced control strategies to two important processes in steel making, namely pulverized coal injection (PCI) in blast furnaces and LD converters. Firstly, an LQ multivariable controller with gas leakage detection system for PCI vessels is designed and analyzed. Secondly, a foam level control system for the LD converter process using an audio signal for measurement is designed. Thirdly, it is attempted to create a single line flow control system for PCI using a video camera. In the latter two cases the conservative approach of inferring unmeasurable physical quantities from the audio and video sources is used. Moreover, all the designs are tested through implementation or experiments at the industrial plant. The control and gas leakage detection system ended up as a full-scale industrial implementation, whereas the projects comprising audio and video information is still at an experimental stage. Work with implementation and experiments pays off in experiences and further insights in the application of control theory, and reveals weaknesses and gaps in the existing theory. Thus, application-driven projects lead to practical solutions and at the same time pose new theoretical challenges. Consequently, this chain of events is favorable to both practitioners and theoreticians, and in turn stimulates the collaboration of industry and academia. Unfortunately, in many research projects this sequence is reversed which complicates technology transfer into industry. As a spin-off effect from the multivariable control project of the PCI process two topics are addressed anew. In the problem of measurement/actuator pairs assignment for decentralized control, the geometrical background of Gramian-based interaction measures is clarified. It is shown that weighted Gramian-based interaction measures can be effectively used for control structure design. In control structure improvement of multivariable control systems, it is shown that improvement potentials can be deduced from coarse models of the closed-loop system. Finally, in the projects comprising audio and video signals in control applications, it is concluded that the theory is rather undeveloped and that these sources should be treated as a multivariable system.Godkänd; 2002; 20061110 (haneit

Multivariable control of a pneumatic conveying system

This licentiate thesis deals with a multivariable controller of a pneumatic conveying system. The industrial process used to illustrate design, analysis and implementation of a multivariable controller is the injection of fine coal into a blast furnace. In the blast furnace process, coke is replaced by fine coal because of economical and environmental reasons. The coal mass flow to the blast furnace becomes a crucial parameter for its operation and hence a control system should be in place to maintain a constant flow. An optimal multivariable linear-quadratic controller has been designed in order to replace the conventional PI-controllers, which were not able to reach the desired control objectives. The design is analyzed by deriving the sensitivity functions of the closed loop system to noise, disturbances and uncertainties. The multivariable controller is then validated through experiments and test operation at the coal injection plant at SSAB Tunnplåt AB in Luleå, Sweden. The reached performance improvements compared with the conventional PI-controllers account for up to 80%. Finally, the controller is combined with a gas-leakage detection system to the commercially available product SafePCI, which is now installed and in operation at SSAB Tunnplåt AB in Luleå, Sweden.Godkänd; 1999; 20061025 (ysko

Intelligent industrial Processes : Automatic Control Perspective

Intelligent Industrial Processes is an area of excellence in research and innovation at Luleå University of Technology (LTU), which was formed to promote multi-disciplinary research and innovation relating to Process Industrial Automation, also referred to as ProcessIT. LTU has a strong track record of research in close collaboration with process industries, where research results have often found their way into products and services strengthening the industries position on the global market.For this area of excellence a road mapping study with respect to Automatic Control research was conducted and is summarized in this white paper. The study shows that current research activities in Automatic Control are very relevant to Intelligent Industrial Processes, dealing with techniques for process understanding (modeling), design and implementation of control systems, and process monitoring, only to mention some.It is concluded that the design and establishment of an Open Research and Innovation Platform is essential for collaborative and multi-disciplinary research in the area. Such a software platform will enable industry partners to more efficiently work with their industrial processes and that in close collaboration with researchers and engineering businesses. At the same time researchers and innovators will have the opportunity to test and validate their results and innovations on real-life cases, enabling a swift exploitation of results. Some key principles for this software platform are the open source, open data and open innovation principles that need to be captured in the platform.The results of that study suggest initial automatic control research activities and a time line for stepping stones towards a full scale implementation of an Open Research and Innovation Platform by 2030.Godkänd; 2014; 20141119 (wolfgang

Pressure and flow control of a pulverized coal injection vessel

This Master's Thesis deals with a model-based pressure and flow control of a fine coal injection vessel for use in the blast furnace injection process. Through a transportation pipe, pulverized coal is conveyed from the coal injection vessel to the blast furnace where it is injected through the tuyeres. Irregularities in the coal mass flow to the blast furnace might cause significant variations in the raw iron quality. Therefore, a control system should be in place to maintain a constant pressure in the injection vessel and a constant coal mass flow from the injection vessel to the blast furnace. By means of system modeling and identification, the structure and behavior of the coal injection vessel have been analyzed. It has been shown that by use of model-based design, the control goals can be achieved and the control performance can be sufficiently improved compared to the conventional PI- controllers. Several dynamic models of the plant have been developed. A number of control strategies are presented and compared by means of simulation studies. The LQG design method is used to design the controllers. All the controllers have been validated through experiments on the coal injection plant at SSAB Tunnplåt in Luleå, Sweden.Validerat; 20101217 (root

Towards incremental control structure optimisation for process control

This paper deals with the optimisation of control structures for multivariable process control systems. Incremental optimisation of control structures is the task of improving the performance of an existing control structure by incrementally introducing or removing dynamic connections in the control structure. A preliminary method for the detection of an improving structural change in an existing control structure is presented. The method is applied to the control of a pulverized coal injection process to show its validity and has proven to give good results.Godkänd; 2007; 20080103 (wolfgang