Open/closed loop bifurcation analysis for identification and model based control of fluidized catalytic crackers

2007 ◽  
pp. 1677-1684
Author(s):  
M.P. Vega ◽  
J.A. Mattos ◽  
L.D. Fernandes ◽  
E.L. Lima
Keyword(s):  
Bifurcation Analysis ◽  
Closed Loop ◽  
Model Based Control ◽  
Model Based

Design of Nonlinear Model-Based Control Using Bifurcation Analysis for Solution Polymerizations Carried Out in Lumped-Distributed Reactors

2017 ◽  
Vol 12 (1) ◽  
pp. 1700028 ◽  
Author(s):  
Márcia P. Vega ◽  
Gabrielle F. M. Oliveira ◽  
Enrique L. Lima ◽  
José Carlos Pinto
Keyword(s):  
Nonlinear Model ◽  
Bifurcation Analysis ◽  
Model Based Control ◽  
Model Based

Model Based Control for Closed Loop Testing of 1-D Engine Simulation Models*

2012 ◽  
Vol 45 (30) ◽  
pp. 482-489 ◽  
Author(s):  
Dariusz Cieslar ◽  
Alex Darlington ◽  
Keith Glover ◽  
Nick Collings
Keyword(s):  
Closed Loop ◽  
Simulation Models ◽  
Model Based Control ◽  
Engine Simulation ◽  
Model Based

Closed Loop Control of Resin Flow in VARTM Using a Multi-Segment Injection Line and Real-Time Adaptive, Model-Based Control

Materials ◽  
2005 ◽  
Author(s):  
Ajit R. Nalla ◽  
James L. Glancey
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Performance Metrics ◽  
Void Formation ◽  
Resin Flow ◽  
Time Model ◽  
Loop Control ◽  
Model Based Control ◽  
Model Based ◽  
Injection Line

To improve process controllability during VARTM, a new resin injection line was designed and tested. The injection line, which consists of multiple segments each independently operated, allows for the control of resin flow to different locations within the mold. Simulation of different injection line configurations for various mold geometries is studied. Performance of a prototype line is quantified with a laboratory size mold used to demonstrate the potential value and benefits of this approach. Specific performance metrics, including resin flow front controllability, total injection time and void formation are used to compare this new approach to conventional VARTM injection methods. Computer-based closed loop controller strategies are designed that use point sensor feedback of resin location. In addition, an adaptive control algorithm that uses a finite element model to provide real-time updates of the injection line configuration is presented. Experimental validation of two different control strategies is presented, and demonstrates that real-time, model-based control is possible in VARTM.

For model-based control design, closed-loop identification gives better performance

Automatica ◽  
1996 ◽  
Vol 32 (12) ◽  
pp. 1659-1673 ◽  
Author(s):  
Håkan Hjalmarsson ◽  
Michel Gevers ◽  
Franky de Bruyne
Keyword(s):  
Closed Loop ◽  
Control Design ◽  
Model Based Control ◽  
Model Based ◽  
Closed Loop Identification

Autoregressive modeling of cycle-to-cycle correlations in homogeneous charge compression ignition combustion

2017 ◽  
Vol 19 (7) ◽  
pp. 790-802 ◽  
Author(s):  
Jakob Andert ◽  
Maximilian Wick ◽  
Bastian Lehrheuer ◽  
Christian Sohn ◽  
Thivaharan Albin ◽  
...  
Keyword(s):  
Steady State ◽  
Real Time ◽  
Autoregressive Model ◽  
Closed Loop ◽  
Homogeneous Charge Compression Ignition ◽  
Compression Ignition ◽  
Model Based Control ◽  
Model Based ◽  
Auto Ignition ◽  
Steady State Operation

Homogeneous charge compression ignition or gasoline controlled auto-ignition combustion is characterized by a strong coupling of consecutive cycles, which is caused by residuals from the predecessor cycle. Closed-loop combustion control is considered a promising technology to actively stabilize the process. Model-based control algorithms require precise prediction models that are calculated in real time. In this article, a new approach for the transient measurement of the auto-ignition process and the data-driven modeling of combustion phasing and load is presented. Gasoline controlled auto-ignition combustion is modeled as an autoregressive process to represent the cycle-to-cycle coupling effects. The process order was estimated by partial autocorrelation analysis of steady-state operation measurements. No significant correlations are found for lags that are greater than one. This observation is consistent with the assumption that cycle coupling is mainly caused by the amount of exhaust gas that is directly transferred to the consecutive combustion. Because steady-state operation results in a hard coupling of actuation and feedback variables, only minor variations of the test data can be achieved. The steady-state tests delivered insufficient data for the generalized modeling of the transient autoregressive effects. A new transient testing and measurement approach is required, which maximizes the variation of the predecessor cycle’s characteristics. Dynamic measurements were performed with the individual actuation of the injection strategy for each combustion cycle. A polynomial model is proposed to predict the combustion phasing and load. The regression analysis shows no overfitting for higher polynomial orders; nevertheless, a first-order polynomial was selected because of the good extrapolation capabilities of extreme outliers. The prediction algorithm was implemented in MATLAB/Simulink and transferred to a real-time-capable engine control unit. The verification of the approach was performed by test bench measurements in dynamic operation. The combustion phasing was precisely predicted using the autoregressive model. The combustion phasing prediction error could be reduced by 53% in comparison to a state-of-the-art mean value-based prediction. This work provides the basis for the development of a closed-loop autoregressive model-based control for gasoline controlled auto-ignition combustion.

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