Adaptive exact linearization control of batch polymerization reactors using a Sigma-Point Kalman Filter

Beyer, Marc-André; Grote, Wolfgang; Reinig, Gunter

doi:10.1016/j.jprocont.2007.12.002

Cited by 30 publications

(27 citation statements)

References 10 publications

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“…In Reference [20], a real-time estimation for concentrations in a distillation column was developed. In Reference [24], a Kalman filter using a Sigma point for a batch polymerization reactor was conducted. In Reference [25], extended Kalman filtering was used to estimate temperature and irradiation for maximum power point tracking of a photovoltaic module.…”

Section: Introductionmentioning

confidence: 99%

Virtual Sensors for Biodiesel Production in a Batch Reactor

et al. 2017

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Fossil fuel combustion produces around 98% of coal emissions. Therefore, liquid and gaseous biofuels have become more attractive due to their environmental benefits. The biodiesel production process requires measurements that help to control and supervise the variables involved in the process. The measurements provide valuable information about the operation conditions and give estimations about the critical variables of the process. The information from measurements is essential for monitoring the state of a process and verifying if it has an optimal performance. The objective of this study was the conception of a virtual sensor based on the Extended Kalman Filter (EKF) and the model of a batch biodiesel reactor for estimating concentrations of triglycerides (TG), diglycerides (DG), monoglycerides (MG), methyl ester (E), alcohol (A), and glycerol (GL) in real-time through measurement of the temperature and pH. Estimation of the TG, DG, MG, E, A, and Gl through this method eliminates the need for additional sensors and allows the use of different types of control. For the performance analysis of the virtual sensor, the data obtained from the EKF are compared with experimental data reported in the literature, with the mean square error of the estimate then being calculated. In addition, the results of this approach can be implemented in a real system, since it only uses measurements available in a reactor such as temperature and pH.

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Section: Introductionmentioning

confidence: 99%

Virtual Sensors for Biodiesel Production in a Batch Reactor

et al. 2017

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“…In this research, a semi-batch polymerization reactor benchmark is considered which is described by Chylla and Haase [8] and used as a benchmark for process control applications. The schematic diagram of the semi-batch polymerization reactor is shown in Fig.1 [8]. It consists of a stirred tank reactor with cooling jacket and a coolant recirculation.…”

Section: The Chylla-haase Benchmark Reactormentioning

confidence: 99%

“…The heat released through the reaction must be removed by circulating cold water through the jacket, where both hot and cold jacket streams are available. When the jacket temperature controller output is between 0 and 50%, the valve is opened and cold water is inserted, and when the jacket controller output is between 50 and 100%, the valve is opened and steam is inserted [8]. …”

Section: The Chylla-haase Benchmark Reactormentioning

confidence: 99%

“…After determining and scaling the input and output vectors of the system, the multivariable NARX is used to represent the non-linear dynamics of the reactor, The maximum lags in the output were selected as 3, the maximum lags in the input is selected as 2, and the maximum time delay in the inputs is selected as 2, as described in Eq. (8). Here again the neural network is realised by a RBF network with Gaussian basis functions.…”

Section: )mentioning

confidence: 99%

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Robust fault diagnosis for an exothermic semi-batch polymerization reactor under open-loop

Ertiame

Feng

et al. 2014

Systems Science & Control Engineering

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Abstract-Fault detection and fault diagnosis have become increasingly important for improvement of the reliability, safety and efficiency of many technical processes. In this research, a new robust fault detection and isolation (FDI) scheme is developed for open-loop Chylla-Haase polymerization reactor. This reactor has been widely used as an industrial Benchmark. The independent Radial Basis Function (RBF) Neural Network (RBFNN) is employed here for on-line diagnosis of faults on the actuator, sensors, and reactor components when the system is subjected to system uncertainties and disturbances. Two different techniques to employ RBF neural networks are investigated. Firstly, an independent neural network is used to model the reactor dynamics and generate residuals. Secondly, an additional RBF neural network is developed as a classifier to isolate faults from the generated residuals. Three sensor faults and one actuator fault are simulated on the Chylla-Haase reactor. Moreover, many practical disturbances and system uncertainties, such as monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise are modelled. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

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“…A global linearization control strategy with online state and parameter estimation was applied for a polymerization reactor in [6]. However, the authors concluded that the implementation of the proposed method is still difficult due to the missing support of required mathematical functions.…”

Section: Introductionmentioning

confidence: 99%

Influence of Online Identification Methods on the Nonlinear Process Control

Macků¹,

Novosad²

2017

DAAAM Proceedings

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Control of systems with strong nonlinearities is impossible or difficult by common linear systems methods. Sometimes the system linearization around the working point can be a solution, but it is not always applicable. Other, better possibility, is using online system identification during the whole process and based on it the controller parameters changing. In this case, the control is closely dependent on the process identification quality. In this paper, the quality of the control process using different identification methods and their settings is observed. A nonlinear process model based on the exothermic semi-batch reactor is used and the whole process is simulated using data of real process. Results are discussed.

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Adaptive exact linearization control of batch polymerization reactors using a Sigma-Point Kalman Filter

Cited by 30 publications

References 10 publications

Virtual Sensors for Biodiesel Production in a Batch Reactor

Virtual Sensors for Biodiesel Production in a Batch Reactor

Robust fault diagnosis for an exothermic semi-batch polymerization reactor under open-loop

Influence of Online Identification Methods on the Nonlinear Process Control

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