Multiple-Model Internal Model Control of Main Steam Temperature with a Hybrid Model Scheduling Strategy

Author(s):  
Weiwei Chen ◽  
Lihui Cen ◽  
Ankang Cao
2012 ◽  
Vol 507 ◽  
pp. 91-95
Author(s):  
Jun Li ◽  
Wei Wei Li ◽  
Peng Qi ◽  
Qing Bin Yu

Principles and characteristics of internal model control (IMC) are illustrated. It has a simple and general structure such as that of a PID controller. Applications of IMC based on single loop PID controller tuning in main steam temperature of boiler in power plant were investigated. It can also become easier to achieve in a distributed control system (DCS) via control module configuration. It was applied in boiler of power plant to tune the main steam temperature PID parameters. The application results demonstrate the validity of the proposed method.


2013 ◽  
Vol 732-733 ◽  
pp. 864-869
Author(s):  
Wei Lu ◽  
Ming Chun Wang

This paper proposes a novel Internal Model Control (IMC) method for the control of superheater steam temperature. The IMC is known for good robustness including handling of systems with time delays. While Iterative Learning Control (ILC) is a strategy for dealing with periodic disturbances. By using a combination of IMC and ILC, their individual advantages are used to increase the robustness against modeling uncertainties and handling time as well as decreasing the influence of the periodic disturbances affecting the superheater steam. Some simulation examples are shown to illustrate performance improvements that can be achieved by the new method over the conventional IMC and PID methods. Key Words: Superheater Steam Temperature; Internal Model Control; Iterative Learning Control


Author(s):  
Seungwoo Hong ◽  
Inseok Park ◽  
Myoungho Sunwoo

This paper proposes a model-based gain scheduling strategy of a Skogestad internal model control (SIMC)-based boost pressure controller for passenger car diesel engines. This gain scheduling strategy is proposed with a new scheduling variable to handle the nonlinear variable geometric turbocharger (VGT) plant characteristics. The scheduling variable is derived from the pressure ratio between the exhaust and intake manifolds and the exhaust air-to-fuel ratio to estimate the static gain of the VGT plant, which varies widely with change in the engine operating conditions. The proposed static gain model was designed with the scheduling variable, engine speed, and fuel injection quantity. Compared to the steady-state experimental data, the static gain model showed an R-squared value of 0.91. The boost pressure controller had the proportional-integral (PI) structure to allow for online calibration, and the PI gains were determined using the SIMC method. The proposed static gain model for the VGT plant was integrated into the SIMC control structure to obtain the appropriate control gains under wide engine operating area. The proposed control algorithm was compared with a fixed gain boost pressure controller through various step tests of the desired boost pressure. The fixed gain controller showed a large overshoot of 64% when the exhaust gas recirculation (EGR) operating condition was changed. In contrast, the proposed gain scheduled boost pressure controller reduced the overshoot to 12%. The model-based gain scheduling strategy successfully adjusted the control gains to achieve consistent control performance under various engine operating conditions.


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