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This article mainly focuses on two treatment methods in FIR model identification for the abnormality in measured data set. One is called linear interpolation method(LIM), whose essence is to rebuild the data set according to linear interpolation after indicating the abnormal data. The other is the method of identification based on segments of data(ISDM). The idea is to remove the abnormal data and...
Based on the sampled data of a sinusoidal signal corrupted by unknown constant bias and noise with non-zero mean, a simple and novel approach is proposed to reconstruct the sinusoidal signal having same frequency as the original signal but free from unknown constant bias.Moreover, the noisy component of reconstructed signal have a zero mean no matter what the mean value of noisy component of original...
Atmospheric 3rd line diesel oil solidifying point is an important quality index, which cannot be measured in real time, in petroleum industry. Due to the great nonlinear characteristic of distillation columns, common statistic methods, such as PCR and PLS, based on linear projection, are not able to estimate such a quality index effectively. In this paper, Adaptive kernel based Relevance Vector Machine...
Computational methods for designing an optimal catalyst have recently been gaining more popularity in the fields of catalysis and reaction engineering of energy systems. However, in general, the problem in these approaches is that uncertainties present in process models should be handled correctly to achieve a robust design. To find the optimal design under these uncertainties, a stochastic optimization...
A data reconciliation with simultaneous bias and leak estimation approach is proposed in this paper, which is based on combining merits of the generalized T distribution method and the extended Akaike information criterion (AIC) method proposed in this paper. This approach makes use of GT distribution function to eliminate the effects of measurement biases and applies extended AIC approach to address...
This paper considers the optimal boundary control of reaction-diffusion process with time-varying spatial domain in the context of the Czochralski crystal growth process. A parabolic partial differential equation (PDE) model of the reaction-diffusion process which preserves the dynamical features attributed to the time-varying spatial domain is developed. The parabolic PDE is coupled to a second order...
The requirement of hydrogen in oil refineries is increasing as market forces and environmental legislation, so the management and optimization of hydrogen system in refineries is becoming increasingly more important. In this paper, an improved approach for the optimization of hydrogen network is proposed. The method decomposes the optimization problem into two sub-problems, the optimization of feed...
Considering the mount of high temperature steam consumed in the evaporation process is large, which is much higher than designed value, an optimization model is established to minimize steam consumption per ton of evaporated water. It focuses on operation optimization of evaporation process and takes into account a wide range of operating conditions and system configurations. And a new vortex motion...
Refrigeration systems consume a substantial amount of energy. Taking for instance supermarket refrigeration systems as an example they can account for up to 50–80% of the total energy consumption in the supermarket. Due to the thermal capacity made up by the refrigerated goods in the system there is a possibility for optimizing the power consumption by utilizing load shifting strategies. This paper...
In this work, a new method to control the processes with the unmeasured input disturbance and random noise parametric uncertainty is proposed. The control structure of two-degree-of-freedom is used for enhancing the setpoint regulation and the load disturbance rejection. The tracking controller is designed by input/output linearization technique with the disturbance-free model. Based on the high gain...
In this paper, A model reference adaptive compound control algorithm is proposed for the test turntable system with unknown or slowly time-variant parameters. The combination of the general classical feedback correction and the adaptive feedforward compensation can ensure that the test turntable system always gets good performance of the output tracking the input and retains the capability of disturbances...
Nowadays general-purpose process plant simulators are used widely in industry and in academia, reason being process model can be developed more rigorously with fewer endeavors and the graphical user interface makes the realization of model less time consuming. During the development phase of a process model we often have a lot of variables that has to vary to get the best solution among several candidates...
In this paper, an enhanced robust fault diagnosis scheme is provided for the non-Gaussian stochastic distribution systems (SDSs). The available driven information for fault diagnosis is the probability density functions (PDFs) or the statistic information set of the output rather than the output value. A mixed neural network (NN) model with modeling error is established, where a static NN is applied...
Manufacturing industry needs a more effective and unified information system to meet market demand changes and societal/environmental requirements. The international standard ISO/IEC 62264 (an adoption of ISA SP95) presents an integrated framework for business planning & logistics, manufacturing operation management, and control. The information system integration models proposed in this standard...
Refining units are easy to be flammable and explosive. There will be great security risk in applying advanced process control (APC) system online in refining units. The method of HSE management, which emphasizes hazard analysis and risk control, will greatly decrease the possibility of the risk of the APC project. Experiences in previous APC projects and HSE management method are summarized in this...
This paper deals with a design problem of an anti-windup adaptive PID control system for SISO systems. The proposed method utilizes the characteristics of almost strict positive realness (ASPR) of the controlled system. the windup phenomenon will be improved by reducing the magnitude of adaptive gains in integral and derivative action, when the controlled input is saturated. The effectiveness of the...
State and parameter estimation are cornerstone problems in Chemical Process Control. When the problem is linear and gaussian, the celebrated Kalman Filter provides a simple and elegant solution to the recursive filtering problem. However, many practical systems (including most Chemical Processes) are nonlinear. In this case, the Kalman Filter cannot be directly applied and other methods are necessary...
The performance of Bayesian state estimators is dependent on accurate characterisation of the uncertainties in the unmeasured disturbances and in the measurements. The structure of the unmeasured disturbance dynamics is seldom known. Moreover, the disturbances could be correlated in time. In this work a constrained optimisation problem based on the MLE framework is presented to identify the dynamics...
In this paper, we propose a method for state estimation of nonlinear systems represented by Takagi-Sugeno (T-S) models with unmeasurable premise variables. The main result is established using the differential mean value theorem which provides a T-S representation of the differential equation generating the state estimation error. This allows to extend some results obtained in the case of measurable...
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