This paper studies the state feedback stabilization of LTI plants over wireless block-fading channels. The packet-loss rate of each channel depends on power level and packet length used for transmission as well as cha...
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This paper studies the state feedback stabilization of LTI plants over wireless block-fading channels. The packet-loss rate of each channel depends on power level and packet length used for transmission as well as channel power gain. Different from the case of fixed packet-loss rate, the packet-loss rate considered in this paper is random and time-varying as the channel power gain is so for wireless communication. When power level and packet length are assumed to be time-invariant for every transmission at each channel, necessary and sufficient conditions for mean square stabilizability via state feedback are given in terms of the unstable poles of the plant. The performance defined as the asymptotic mean square norm of the system state is also discussed for the scalar case.
Predicting the best shutdown time of a steam ethylene cracking furnace in industrial practice remains a challenge due to the complex coking process. As well known, the shutdown time of a furnace is mainly determined b...
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Predicting the best shutdown time of a steam ethylene cracking furnace in industrial practice remains a challenge due to the complex coking process. As well known, the shutdown time of a furnace is mainly determined by coking condition of the transfer line exchangers (TLE) when naphtha or other heavy hydrocarbon feedstocks are cracked. In practice, it is difficult to measure the coke thickness in TLE through experimental method in the complex industrial situation. However, the outlet temperature of TLE (TLEOT) can indirectly characterize the coking situation in TLE since the coke accumulation in TLE has great influence on TLEOT. Thus, the TLEOT could be a critical factor in deciding when to shut down the furnace to decoke. To predict the TLEOT, a paramewic model was proposed in this work, based on theoretical analysis, mathematic reduction, and parameters estimation. The feasibility of the proposed model was further checked through industrial data and good agreements between model prediction and industrial data with maximum deviation 2% were observed.
Filtering and feature extraction are very important in the analysis and study of EEG signal under +Gz acceleration. In this study, a new filter of different frequency characteristics of EEG signal under +Gz accelerati...
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This paper focuses on performance improvements of the permanent magnet synchronous motor (PMSM) vector control. In this paper, a novel second order sliding mode control (SOSMC) algorithm is presented to accomplish vel...
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A three dimensional vision sensing system was used to mimic the human vision system to observe the three-dimensional weld pool surface in pipe Gas Tungsten Arc Welding (GTAW) process. Novel characteristic parameters c...
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Optimizing operation parameters for Texaco coal-water slurry gasifier with the consideration of multiple objectives is a complicated nonlinear constrained problem concerning 3 BP neural networks. In this paper, multio...
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Production scheduling is an important aspect of batch process operations to achieve high productivity and operability. In this paper, we considered a zero-wait multiproduct scheduling with due dates under uncertainty,...
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Common spatial pattern(CSP) has been one of the most popular methods for EEG feature extraction in brain-computer interface(BCI) application. Although the CSP usually provides good discriminant features for classifica...
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Common spatial pattern(CSP) has been one of the most popular methods for EEG feature extraction in brain-computer interface(BCI) application. Although the CSP usually provides good discriminant features for classification,it is also known to be sensitive to overfitting and *** study introduces a shrinkage technique to regularize estimation of the covariance matrices in the CSP and hence a novel shrinkage CSP(SCSP) method,which could effectively alleviate the effects of small training sample size and unbalanced data on classification. The proposed SCSP is validated on feature extraction of P300 that has been widely adopted for BCI *** accuracies are evaluated by using linear discriminant analysis(LDA) with experimental EEG data from seven *** results indicate that the proposed SCSP extracts more effective features that yield higher classification accuracy than that by the traditional CSP.
Intelligent procedure expert system was developed to select appropriate GTAW procedure in this ***,the function design and implementation methods of the welding procedure expert system were *** expert system can prese...
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Intelligent procedure expert system was developed to select appropriate GTAW procedure in this ***,the function design and implementation methods of the welding procedure expert system were *** expert system can present the welding procedure card,multimedia display of welding process,and output function to makes the data sharing more ***,the database design of the welding procedure expert system based on C/S mode was presented where the expert knowledge was *** last,the neural network model was established to realize procedure selection based on the neural network learning ability and the welding case from the *** the BPNN model,the welding parameters can be obtained based on the input welding conditions.
This paper studies the scheduling problem in a permutation flow shop with the objective of makespan, which is known as one of major problems in the field of scheduling. In order to solving the corresponding model, an ...
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This paper studies the scheduling problem in a permutation flow shop with the objective of makespan, which is known as one of major problems in the field of scheduling. In order to solving the corresponding model, an improved shuffled frog leaping algorithm(ISFLA) is put forward for this kind of scheduling problem. A new leaping rule based on the characteristic of the problem is devised to improve the performance of the ISFLA. And it can not only produce feasible solutions but also maintain the structure characteristic of the SFLA. Computational experiments on benchmark sets show that the proposed ISFLA is greatly effective to generate good solutions relative to the other two algorithms.
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