In this paper,a novel dimensionality reduction method,time space coordinated-locality preserving projections(TSCLPP) is proposed based on locality preserving projection(LPP).For the short sampling interval,except the ...
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In this paper,a novel dimensionality reduction method,time space coordinated-locality preserving projections(TSCLPP) is proposed based on locality preserving projection(LPP).For the short sampling interval,except the data correlation in spatial scale,there exists data correlation in time scale as *** considering the correlation of sampling points in time and spatial scale simultaneously,TSCLPP constructs the adjacency graph by selecting adjacent points in time-sequence and Euclidean distance ***,the importance of the time-sequential neighbors is measured by the weight based on a time distance.A dual objective function with a weight index coordinating the relationship between time and space is constructed to compute the transformation ***'s T2 and squared prediction error(SPE) are established for process monitoring.A numerical case and the Tennessee-Eastman process(TEP) are employed for the experimental verification.
This paper applies the recently developed framework for integral control on nonlinear spaces to two non-standard cases. First, we show that perfect target stabilization in presence of actuation bias holds also if this...
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Set stabilization for Boolean networks which is a kind of genetic regulatory networks is considered in this paper. An algorithm is provided to achieve the set stability for Boolean networks by changing the columns of ...
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ISBN:
(纸本)9781509009107
Set stabilization for Boolean networks which is a kind of genetic regulatory networks is considered in this paper. An algorithm is provided to achieve the set stability for Boolean networks by changing the columns of the transition matrices of Boolean networks. Then, pinning nodes can be selected. Furthermore, pinning control design algorithm is given. Finally, the model for infection of the bacterium is presented to illustrate the effectiveness of the proposed results.
It is well known that feedback failure increases operating errors in control systems. The objective here is to develop controllers that reduce such operating errors in minimal time, once feedback has been restored. It...
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This paper studies the input-output finite-time stabilization problem of a class of fuzzy stochastic systems with randomly occurring uncertainties and (x, u)-dependent noises. By considering the randomly occurring gai...
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ISBN:
(纸本)9781467384155
This paper studies the input-output finite-time stabilization problem of a class of fuzzy stochastic systems with randomly occurring uncertainties and (x, u)-dependent noises. By considering the randomly occurring gain fluctuations in controller gains, a fuzzy controller is designed to render the closed-loop system input-output finite-time stochastic stability with respect to some specified parameters. Through intensive stochastic analysis, a sufficient condition is established for the controller design via a convex optimization approach. A numerical example is exploited to demonstrate the effectiveness of the proposed design method.
The robust exponential stability and L-gain analysis of the uncertain switched nonlinear cascade systems with time varying delay are considered in this ***,a sufficient condition for robustly exponential stability is ...
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ISBN:
(纸本)9781509009107
The robust exponential stability and L-gain analysis of the uncertain switched nonlinear cascade systems with time varying delay are considered in this ***,a sufficient condition for robustly exponential stability is studied by using the average dwell-time method,piecewise Lyapunov function and free weighting matrix approach,and then the L-gain of the uncertain switched nonlinear cascaded systems with the external disturbance is ***,the switching law and the average dwell-time are ***,a numerical example is provided to illustrate the effectiveness of the proposed results.
An ethylene plant's main purpose is to convert hydrocarbon feedstock,usually natural gas liquids or naphtha,into a "cracked gas" that contains ethylene and other higher value products,by breaking carbon-...
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An ethylene plant's main purpose is to convert hydrocarbon feedstock,usually natural gas liquids or naphtha,into a "cracked gas" that contains ethylene and other higher value products,by breaking carbon-carbon bonds in the *** process also results in the slow deposition of coke,a form of carbon,on the reactor *** coke layer on the internal tube skin reduces the cross section of the reactor tube,increases the pressure drop and also degrades the efficiency of the *** characteristic that continuous operational performance of cracking furnaces gradually decays within time brings challenge to the operational scheduling for the entire furnace *** it's normally time-consuming to develop a new process model for multiple feeds and different cracking furnaces in the new process *** this paper,a transfer learning method based on time series is proposed for fast modeling ethylene yields from the view of common characteristics that ethylene yield decays over *** to previous studies,the new model allows to take advantage of a small amount of newly labeled data to construct a high-quality prediction model for the new ***,it obtains satisfied short-term forecast *** studies demonstrate the efficacy of the developed methodology.
A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rat...
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A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
A multivariate method for fault diagnosis and process monitoring is proposed. This technique is based on a statistical pattern(SP) framework integrated with a self-organizing map(SOM). An SP-based SOM is used as a cla...
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A multivariate method for fault diagnosis and process monitoring is proposed. This technique is based on a statistical pattern(SP) framework integrated with a self-organizing map(SOM). An SP-based SOM is used as a classifier to distinguish various states on the output map, which can visually monitor abnormal states. A case study of the Tennessee Eastman(TE) process is presented to demonstrate the fault diagnosis and process monitoring performance of the proposed method. Results show that the SP-based SOM method is a visual tool for real-time monitoring and fault diagnosis that can be used in complex chemical *** with other SOM-based methods, the proposed method can more efficiently monitor and diagnose faults.
Brain-computer interface (BCI) can help patients who lost control over most muscles but are still conscious to communicate or interact with the environment. In the offline experiment, all the subjects have to do is co...
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ISBN:
(纸本)9781509012251
Brain-computer interface (BCI) can help patients who lost control over most muscles but are still conscious to communicate or interact with the environment. In the offline experiment, all the subjects have to do is counting the target stimulus when they were using the visual-evoked event-related potential (ERP) based BCIs. The recorded electroencephalogram (EEG) data was used to train the classification mode. However, subjects may get distracted in counting the target stimulus when the non-target stimulus affected the subjects or subjects lost their attentions which may negatively affect the task performance. In this study, some green flashing points was added into the stimuli. The subjects have to focus on the target stimulus and count the number of the green points in target stimulus at the same time. In this way, it will make subjects concentrate more on the target to count the green points compared to the pattern without green points. The result showed that the performance of the BCI system could be improved using the method presented in this paper.
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