Aiming at a kind of uncertainties of models in complex industry processes, a novel method for selecting robust parameters is stated in the paperBased on the analysis, parameters selecting for robust control is reduced...
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Aiming at a kind of uncertainties of models in complex industry processes, a novel method for selecting robust parameters is stated in the paperBased on the analysis, parameters selecting for robust control is reduced to be an object optimization problem, and the particle swarm optimization(PSO) is used for solving the problem, and the corresponding robust parameters are obtainedSimulation results show that the robust parameters designed by this method have good robustness and satisfactory performance.
The problem of on-line parameter identification was discussed for linear multivariable discrete time stochastic systems with communication access constraints. Based on the concept of parameter estimability defined wit...
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The problem of on-line parameter identification was discussed for linear multivariable discrete time stochastic systems with communication access constraints. Based on the concept of parameter estimability defined with mutual information, a condition for identifiability was proved under the assumption that the time-varying parameter can be modeled as a Gauss-Markov process, and the sensors access status is described by binary-value function. Analytical analysis and simulation results show that, there is a proper communication strategy which preserving the identifiability of the system under access constraints.
Principal component analysis (PCA) is very suitable for complex process monitoring and diagnosis, but it suffers many limitations such as great calculation load, poor real-time performance and lacking of on-line monit...
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Principal component analysis (PCA) is very suitable for complex process monitoring and diagnosis, but it suffers many limitations such as great calculation load, poor real-time performance and lacking of on-line monitoring. Here, this paper presents a new method for multi-variable statistical process monitoring. Based on this new method, the principal component monitoring model can be generated in the principal component subspace, and the error monitoring model can be set up in the residual subspace. The method provides a human-machine monitoring interface and related fault-diagnosis interface for integrating Principal/Error/Multi-variable. This will change the real-time data of the multi-variable into the monitoring information of an integrated process, and present them effectively to the operators. With this method, on-line monitoring system was designed for the distillation process as an example, and the effectiveness of this method was illustrated.
Aiming at the business competition in the global market, how to real-timely monitor the dynamic trends of supply chain in the market has been a difficulty of supply chain management. By putting into several levels of ...
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ISBN:
(纸本)9781424473311
Aiming at the business competition in the global market, how to real-timely monitor the dynamic trends of supply chain in the market has been a difficulty of supply chain management. By putting into several levels of monitoring process of the supply chain, we developed a method for the information system of supply chain monitoring on the basis of the IDEF model. With this method, one would expect to detect unexpected variations at an early stage and to give early-warnings for potential risks. The enterprises would have enough time to respond to unwanted situations, to take preventive decisions and to meet efficiently the market demands.
A sparse approximation algorithm based on projection is presented in this paper in order to overcome the limitation of the non-sparsity of least squares support vector machines (LS-SVM). The new inputs are projected...
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A sparse approximation algorithm based on projection is presented in this paper in order to overcome the limitation of the non-sparsity of least squares support vector machines (LS-SVM). The new inputs are projected into the subspace spanned by previous basis vectors (BV) and those inputs whose squared distance from the subspace is higher than a threshold are added in the BV set, while others are rejected. This consequently results in the sparse approximation. In addition, a recursive approach to deleting an exiting vector in the BV set is proposed. Then the online LS-SVM, sparse approximation and BV removal are combined to produce the sparse online LS-SVM algorithm that can control the size of memory irrespective of the processed data size. The suggested algorithm is applied in the online modeling of a pH neutralizing process and the isomerization plant of a refinery, respectively. The detailed comparison of computing time and precision is also given between the suggested algorithm and the nonsparse one. The results show that the proposed algorithm greatly improves the sparsity just with little cost of precision.
The objective of this paper is to propose a universal methodology for performance assessment of run-to-run control in semiconductor manufacturing. The slope of the linear semiconductor process model is assumed to be k...
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The objective of this paper is to propose a universal methodology for performance assessment of run-to-run control in semiconductor manufacturing. The slope of the linear semiconductor process model is assumed to be known or subjected to mild plant/model mismatch. Based on an internal model control framework, analytical expressions of minimum variance performance (MVP) and best achievable performance (BAP) for a series of run-to-run control schemes are derived. In the methodology, closed-loop identification is utilised as the first step to estimate the noise dynamics via routine operating data, and numerical optimisation is employed as a second step to calculate the best achievable performance bounds of the run-to-run control loops. The validity of the methodology is justified by examples of performance assessment for EWMA control, double EWMA control and RLS-LT control, even under circumstances where the processes encounter model mismatch, metrology delay and more sophisticated noises. Several essential characteristics of run-to-run control are discovered by performance assessment, and valuable advice is offered to process engineers for improving the run-to-run control performance. Furthermore, a useful application example for online performance monitoring and optimal tuning of run-to-run controller demonstrates the advantage of the methodology.
Based on the reported reaction networks,a novel six-component hydroisomerization reaction net-work with a new lumped species including C_(8)-naphthenes and C_(8)-paraffins is proposed and a kinetic model for a commerc...
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Based on the reported reaction networks,a novel six-component hydroisomerization reaction net-work with a new lumped species including C_(8)-naphthenes and C_(8)-paraffins is proposed and a kinetic model for a commercial unit is also *** empirical catalyst deactivation function is incorporated into the model accounting for the loss in activity because of coke forma-tion on the catalyst surface during the long-term *** Runge-Kutta method is used to solve the ordinary differential equations of the *** reaction kinetic parameters are benchmarked with several sets of balanced plant data and estimated by the differential vari-able metric optimization method(BFGS).The kinetic model is validated by an industrial unit with sets of plant data under different operating conditions and simulation results show a good agreement between the model predic-tions and the plant observations.
A short historical view of process automation in China is provided. The development of essential aspects of process automation, including Distributed control System (DCS), advancedprocesscontrol (APC) and Manufactur...
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A short historical view of process automation in China is provided. The development of essential aspects of process automation, including Distributed control System (DCS), advancedprocesscontrol (APC) and Manufacturing Execution System (MES), are discussed in detail. The contribution of local process automation companies, i.e. SUPCON, and HOLLYSYS are highlighted.
This paper describes an experimental platform which is useful for graduate and undergraduate education in control engineering. It contains a six-tank liquid level regulation system and a pilot distillation column, whi...
This paper describes an experimental platform which is useful for graduate and undergraduate education in control engineering. It contains a six-tank liquid level regulation system and a pilot distillation column, which can be used as stand-alone apparatus. Some extensions of the apparatus are made to increase the function of the platform. The compositions of distillate can be estimated by adding soft sensors to the distillation column. Integrating with liquid level regulation system makes the inlet and outlet flow of the distillation column controllable which provides a realistic engineering experimental environment. It is possible to describe the impacts of unloading from upstream and charging to downstream as in process industry. The platform has been used for graduate courses such as system identification, soft sensor designing and advancedcontrol system.
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