Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks...
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Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithm framework which has a population space, a medium space and a belief space is firstly conceived. Standard differential evolution algorithm(DE), genetic algorithm(GA), and particle swarm optimization algorithm(PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/PSO(3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms(EAs) can be improved,and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.
In this paper, an improved hybrid particle swarm optimization (IHPSO) method, which is able to handle the equality constraints efficiently, has been proposed to determine the optimal recipe offline for the gasoline bl...
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In this paper, an improved hybrid particle swarm optimization (IHPSO) method, which is able to handle the equality constraints efficiently, has been proposed to determine the optimal recipe offline for the gasoline blending process. In addition, the proposed method has been applied onsite in a gasoline production line in Nanjing, China. The results show that the optimized recipes are able to improve the first-time success rate for the blending process and decrease the quality giveaways and blending cost significantly.
This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems(S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions(S-TPMFs) o...
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This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems(S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions(S-TPMFs) of discrete-time semi-Markov chains are no longer confined to the geometric distribution, and it is difficult to obtain accurate and comprehensive information for S-TPMFs in practice. This is because S-TPMFs are usually deduced from the statistical characteristics according to the sampled-data, while adequate samples are often costly and time consuming. In this study, when the S-TPMFs for semi-Markov chains are assumed to be unavailable, the σ-error mean square stability is investigated for discrete-time S-MJLSs with some widely used assumptions; for semi-Markov chains, only the transition probability matrix of the embedded chain is used. In addition, the existence conditions of the effective controller are provided for closed-loop systems without using the information of S-TPMFs. Numerical examples are presented to illustrate the validity of the obtained theoretical results.
This paper is concerned with synchronization in a network with two different types of interactions, formulated by multilayer networks. A switching law between the two layers is proposed, which follows a Bernoulli dist...
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This paper studies the consensus problem of general linear multi-agent systems via self-triggered control. Two distributed self-triggered control schemes based on state feedback and output feedback are developed respe...
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This paper studies the consensus problem of general linear multi-agent systems via self-triggered control. Two distributed self-triggered control schemes based on state feedback and output feedback are developed respectively. It is shown that under the proposed control protocols, consensus can be reached if the communication graph of the multi-agent system is *** example is presented to illustrate the effectiveness of the proposed control methods.
Because static soft sensor modeling can not reflect the dynamic information of industrial processes, which lead to worse estimation precision and robustness. A dynamic soft sensor modeling based on least square vector...
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In this paper, a robust iterative learning control (ILC) designed through a linear matrix inequality (LMI) approach is proposed first, based on the worst-case performance index with ellipsoidal uncertainty and polytop...
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This paper deals with the H ∞ filter design problem for event-triggered networked control systems (NCSs), where the next task release time and finishing time are predicted based on the sampled states. The closed-loo...
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This paper deals with the H ∞ filter design problem for event-triggered networked control systems (NCSs), where the next task release time and finishing time are predicted based on the sampled states. The closed-loop filtering error system is modeled as a linear system with an interval time-varying delay and event-triggered communication strategy. Based on this model, some novel criteria for the asymptotic stability analysis and H ∞ filter design of the event-triggered NCSs with time-varying delay are established to guarantee a prescribed H ∞ disturbance rejection attenuation level. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.
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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ISBN:
(纸本)9781467376808
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 pay attention not only to the target stimulus, but also to the real control target which would bring high workload to users and affect the control efficiency of BCI systems. In this paper, a real-time monitoring system was developed to solve this problem by showing the environment information from the camera on the computer screen. Five subjects took part in this experiment and all of them were asked to control a small car to the target position. Our result showed that all subjects could finish the task within two or three minutes. In this study, subject did not need to switch their attention on the car which was out of their sight, and it would help to improve the usability of BCI in the practical application.
This paper studies global synchronization between a heterogeneous dynamical network and a known target trajectory via distributed impulsive control. Synchronization with an error level, called quasi-synchronization, i...
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