<p>The Stressometer system is a measurement and control system used in cold rolling to improve the flatness of a metal strip. In order to achieve this goal the system employs a multiple input multiple output (MIMO) control system that has a considerable number of sensors and actuators. As a consequence the computational load on the Stressometer control system becomes very high if too advance functions are used. Simultaneously advances in rolling mill mechanical design makes it necessary to implement more complex functions in order for the Stressometer system to stay competitive. Most industrial players in this market considers improved computational power, for measurement, control and modeling applications, to be a key competitive factor. Accordingly there is a need to improve the computational power of the Stressometer system. Several different approaches towards this objective have been identified, e.g. exploiting hardware parallelism in modern general purpose and graphics processors.</p><p>Another approach is to implement different applications in FPGA-based hardware, either tailored to a specific problem or as a part of hardware/software co-design. Through the use of a hardware/software co-design approach the efficiency of the Stressometer system can be increased, lowering overall demand for processing power since the available resources can be exploited more fully. Hardware accelerated platforms can be used to increase the computational power of the Stressometer control system without the need for major changes in the existing hardware. Thus hardware upgrades can be as simple as connecting a cable to an accelerator platform while hardware/software co-design is used to find a suitable hardware/software partition, moving applications between software and hardware.</p><p>In order to determine whether this hardware/software co-design approach is realistic or not, the feasibility of implementing simulator, computational and control applications in FPGAbased hardware needs to be determined. This is accomplished by selecting two specific applications for a closer study, determining the feasibility of implementing a Stressometer measuring roll simulator and a parallel Cholesky algorithm in FPGA-based hardware.</p><p>Based on these studies this work has determined that the FPGA device technology is perfectly suitable for implementing both simulator and computational applications. The Stressometer measuring roll simulator was able to approximate the force and pulse signals of the Stressometer measuring roll at a relative modest resource consumption, only consuming 1747 slices and eight DSP slices. This while the parallel FPGA-based Cholesky component is able to provide performance in the range of GFLOP/s, exceeding the performance of the personal computer used for comparison in several simulations, although at a very high resource consumption. The result of this thesis, based on the two feasibility studies, indicates that it is possible to increase the processing power of the Stressometer control system using the FPGA device technology.</p>

The Stressometer system is a measurement and control system used in cold rolling to improve the flatness of a metal strip. In order to achieve this goal the system employs a multiple input multiple output (MIMO) control system that has a considerable number of sensors and actuators. As a consequence the computational load on the Stressometer control system becomes very high if too advance functions are used. Simultaneously advances in rolling mill mechanical design makes it necessary to implement more complex functions in order for the Stressometer system to stay competitive. Most industrial players in this market considers improved computational power, for measurement, control and modeling applications, to be a key competitive factor. Accordingly there is a need to improve the computational power of the Stressometer system. Several different approaches towards this objective have been identified, e.g. exploiting hardware parallelism in modern general purpose and graphics processors. Another approach is to implement different applications in FPGA-based hardware, either tailored to a specific problem or as a part of hardware/software co-design. Through the use of a hardware/software co-design approach the efficiency of the Stressometer system can be increased, lowering overall demand for processing power since the available resources can be exploited more fully. Hardware accelerated platforms can be used to increase the computational power of the Stressometer control system without the need for major changes in the existing hardware. Thus hardware upgrades can be as simple as connecting a cable to an accelerator platform while hardware/software co-design is used to find a suitable hardware/software partition, moving applications between software and hardware. In order to determine whether this hardware/software co-design approach is realistic or not, the feasibility of implementing simulator, computational and control applications in FPGAbased hardware needs to be determined. This is accomplished by selecting two specific applications for a closer study, determining the feasibility of implementing a Stressometer measuring roll simulator and a parallel Cholesky algorithm in FPGA-based hardware. Based on these studies this work has determined that the FPGA device technology is perfectly suitable for implementing both simulator and computational applications. The Stressometer measuring roll simulator was able to approximate the force and pulse signals of the Stressometer measuring roll at a relative modest resource consumption, only consuming 1747 slices and eight DSP slices. This while the parallel FPGA-based Cholesky component is able to provide performance in the range of GFLOP/s, exceeding the performance of the personal computer used for comparison in several simulations, although at a very high resource consumption. The result of this thesis, based on the two feasibility studies, indicates that it is possible to increase the processing power of the Stressometer control system using the FPGA device technology.