The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tu...
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The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the "excellent" infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained.
Purified terephthalic acid(PTA) is an important chemical raw material. P-xylene(PX) is transformed to terephthalic acid(TA) through oxidation process and TA is refined to produce PTA. The PX oxidation reaction is a co...
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Purified terephthalic acid(PTA) is an important chemical raw material. P-xylene(PX) is transformed to terephthalic acid(TA) through oxidation process and TA is refined to produce PTA. The PX oxidation reaction is a complex process involving three-phase reaction of gas, liquid and solid. To monitor the process and to improve the product quality, as well as to visualize the fault type clearly, a fault diagnosis method based on selforganizing map(SOM) and high dimensional feature extraction method, local tangent space alignment(LTSA),is proposed. In this method, LTSA can reduce the dimension and keep the topology information simultaneously,and SOM distinguishes various states on the output map. Monitoring results of PX oxidation reaction process indicate that the LTSA–SOM can well detect and visualize the fault type.
control and regulation of furnace firing is essential to extend the runiength of new and existing furnaces. Accurate Computational Fluid Dynamic simulations of the furnace are essential for this purpose. This requires...
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ISBN:
(纸本)9781510806924
control and regulation of furnace firing is essential to extend the runiength of new and existing furnaces. Accurate Computational Fluid Dynamic simulations of the furnace are essential for this purpose. This requires among others accounting for the detailed geometry of the burners. Also the so-called "shadow effect" 6 arising from the projected shadows between adjacent reactors leads to significant heat flux non-uniformities. This phenomenon is important but its effect on product yields is often ignored as only a single reactor is simulated. For the USC furnace simulated in this work, shadow effects cause a maximum difference in COT of 29 K and a difference in P/E-ratioof 0.1 between two different U-coils in the furnace. In order to obtain more uniform TMT's, COTs and olefin yields for the individual reactors, different furnace optimization methods were compared and their results are discussed. Full furnace CFD simulations prove to be essential in design and during debottlenecking, when aiming for a more uniform COT distribution to the reactors by fuel distribution.
A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the...
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A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.
This paper is concerned with the guaranteed cost filtering problem for discrete-time multi-layer neural networks with unideal measurements and time-varying delays. First, the innovative state space model of multi-laye...
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ISBN:
(纸本)9781509041039
This paper is concerned with the guaranteed cost filtering problem for discrete-time multi-layer neural networks with unideal measurements and time-varying delays. First, the innovative state space model of multi-layer neural networks can be described by the weighted-nonlinear function, which means that there have connections among neural layers. Then, the unideal measurements are made up by combination of random sensor nonlinearity and partial missing measurements, where partial missing measurements is the product of two mutually independent stochastic variables and normal measurements. Moreover, by using proportionate-additive filter and constructing a unified Lyapunov function, a novel criterion is proposed so that the augmented filtering error system achieves robust stability and has a guaranteed cost index. Finally, simulation results are presented to demonstrate the effectiveness of the derived method.
Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthes...
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Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal con figuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation, which ensures the feasibility of con figuration and improves computational ef ficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.
The distributed H ∞ state estimation problem over a filtering network with Markov switching topology is studied in this paper by employing event-triggered strategy. The strategy at each node is built on the output e...
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The distributed H ∞ state estimation problem over a filtering network with Markov switching topology is studied in this paper by employing event-triggered strategy. The strategy at each node is built on the output estimation error of its own and those received from its neighbours. Based on the communication uncertainty of practical networks, switching topology which subjects to a heterogeneous Markov chain is considered in filter design. By utilizing stochastic Markov stability theory, switching topology-dependent filters are designed such that the underlying error system is stochastically stable in mean square and the disturbance rejection attenuation level guarantees an H ∞ performance bound. An illustrative example is presented to show the applicability of the obtained results.
Brain-computer interface (BCI) plays an important role in helping the people with severe motor disability. In event-related potential (ERP) based BCIs, subjects were asked to count the target stimulus in the offline e...
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In this paper, consensus of multi-agent systems containing linear self dynamics is investigated. By considering packet losses, a sampled data protocol with packet losses is considered. A switched systems including sta...
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In this paper, consensus of multi-agent systems containing linear self dynamics is investigated. By considering packet losses, a sampled data protocol with packet losses is considered. A switched systems including stable modes and unstable modes is considered here to describe packet losses. By using the contradiction method and the Lyapunov function method, a sufficient condition on consensus of the multi-agent system under consideration is obtained, where the controller can be solved in the form of convex optimization approaches. In addition, the maximum sampling interval is also given.
Brain computer interface (BCI) could help patients to manipulate external devices based on the specific brain activities. One of the most popular BCI systems is the visual-based BCI system. Mostly, users were asked to...
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