NOX selective catalytic reduction control based on simple models

Dolanč, Gregor; Strmĉnik, Stanko; Petrovĉiĉ, Janko

doi:10.1016/s0959-1524(99)00066-9

Cited by 30 publications

(17 citation statements)

References 9 publications

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“…To protect the environment, the NO x concentration in exhaust gas from stack must be controlled within a limit set by environmental regulations. The most commonly used technology is the selective catalytic reduction method, as in Dolanc et al (2001), which uses ammonia (NH 3 ) to decompose NO x . The purpose of the NO x decomposition (de-NO x ) process control in thermal power plants is to control the NO x within a limit set, while at the same time reducing expensive ammonia (NH 3 ) gas consumption as much as possible.…”

Section: Simulation Studymentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear system modeling and robust predictive control based on RBF-ARX model

Peng

Yang

Gui

et al. 2007

Engineering Applications of Artificial Intelligence

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Section: Simulation Studymentioning

confidence: 99%

“…In Fig. 1, a PID feedback and feedforward controller, whose design approach is similar to Dolanc et al (2001) in the system, and its parameters were well tuned for the entire load range. The predictive controller in Fig.…”

Section: Simulation Studymentioning

confidence: 99%

Nonlinear system modeling and robust predictive control based on RBF-ARX model

Peng

Yang

Gui

et al. 2007

Engineering Applications of Artificial Intelligence

View full text Add to dashboard Cite

“…To protect the environment, the NO x concentration in exhaust gas from stack must be controlled within a limit set by environmental regulations. The most commonly used technology is the selective catalytic reduction method, as in (Dolanc, et al, 2001), which uses ammonia (NH3) to decompose NO x . The purpose of the NO x decomposition (de-NO x ) process control in thermal power plants is to control the NO x within a limit set, while at the same time reducing expensive ammonia (NH3) gas consumption as much as possible.…”

Section: Simulation Studymentioning

confidence: 99%

“…At different load level, the process's dynamic behavior (between the de-NO ( ) w t x device outlet NO x ( ) y t and the total NH3 flow-set 2 ( ) ( ) u t v t + in Fig.1) is also different, and may be represented by a linear model. In Fig.1, a PID feedback and feedforward controller, whose design approach is similar to (Dolanc, et al, 2001), has already existed in the system, and its parameters were well tuned for entire load-varying region. The predictive controller in Fig.1 is the existing PID controller output.…”

Section: Simulation Studymentioning

confidence: 99%

RBF-Arx Model-Based Robust MPC for Nonlinear Systems

Peng

Gui

Zou

et al. 2005

IFAC Proceedings Volumes

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An integrated modeling and robust model predictive control (MPC) approach is proposed for a class of nonlinear systems. First, the nonlinear system is identified off-line by a RBF-ARX model possessing linear ARX model structure and state-dependent Gaussian RBF neural network type coefficients. On the basis of the RBF-ARX model, a combination of a local linearization model and a polytopic uncertain linear parameter-varying (LPV) model are built to approximate the present and the future system's nonlinear behavior respectively. Subsequently, based on the approximate models, a min-max robust MPC algorithm with input constraint is designed for the nonlinear systems. The closed loop stability of the MPC strategy is guaranteed by the use of parameter-dependent Lyapunov function and the feasibility of the linear matrix inequalities (LMIs). Simulation study to a NOx decomposition process illustrates the effectiveness of the modeling and robust MPC approaches proposed in this paper.

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“…The exhaust gas contains several types of hydrocarbon which have different effects on monolith behavior such as NO reduction, oxygen storage in ceria, water-gas shift reaction, etc. [18][19][20].…”

Section: Introductionmentioning

confidence: 99%