Quasi-synchronization of heterogenous dynamic networks is studied by using impulsive control in this paper. The asymmetric network connections are considered. First, the weighted average state is introduced as the vir...
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Quasi-synchronization of heterogenous dynamic networks is studied by using impulsive control in this paper. The asymmetric network connections are considered. First, the weighted average state is introduced as the virtual leader. By defining the synchronization error between the virtual leader and the network node, impulsive quasi-synchronization is analyzed and a criterion is derived to ensure quasi-synchronization in the delayed heterogenous network. Then delayed networks with symmetric connections and delay-free networks are studied, respectively, with simpler conditions obtained. Numerical simulations demonstrate the effectiveness of the derived results.
This paper investigates the problem of event-triggered dual-mode distributed predictive control (DPC) for constrained large-scale linear systems subject to bounded disturbances. Based on input-to-state stability (ISS)...
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This paper investigates the problem of event-triggered dual-mode distributed predictive control (DPC) for constrained large-scale linear systems subject to bounded disturbances. Based on input-to-state stability (ISS) theory, the event-triggering condition involving information of the subsystem itself is derived. A dual-mode predictive control scheme is designed to reduce information exchanges with neighboring subsystems. The upper bound of disturbances for ensuring the recursive feasibility and closed-loop stability are developed. Finally, a simulation example is given to show that the presented method is able to save computation resources and communication resources while guaranteeing the desired control performance.
A novel distributed adaptive output feedback control strategy is developed to solve the cooperative output regulation problem of heterogeneous general linear multi-agent systems(MASs) under switching topology. The pro...
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A novel distributed adaptive output feedback control strategy is developed to solve the cooperative output regulation problem of heterogeneous general linear multi-agent systems(MASs) under switching topology. The proposed control strategy avoids using the minimal non-zero eigenvalue of Laplacian matrix when calculating gain matrix, and the communication topology is assumed to contain a directed spanning tree only frequently. It is shown that individual agents could track external signal asymptotically and achieve disturbance rejection. Ultimately, a simulation is presented to exemplify the effectualness of the main result.
A new method was developed for batch process monitoring in this paper. In the devdopad method, just-in-time learning ( JITL ) and independent component analysis (ICA) were integrated to build JITL-ICA monitoring s...
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A new method was developed for batch process monitoring in this paper. In the devdopad method, just-in-time learning ( JITL ) and independent component analysis (ICA) were integrated to build JITL-ICA monitoring scheme. JITL was employed to tackle with the characteristics of batch process such as inherent time- varying dynamics, multiple operating phases, and especially the case of uneven length stage. According to new coming test data, the most correlated segmentation was obtained from batch-wise unfolded training data by JITL. Then, ICA served as the principal components extraction approach. Therefore, the *** distributed data can also be addressed under this modeling framework. The effectiveness and superiority of JITL-ICA based monitoring method was demonstrated by fed-batch penicillin fermentation.
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.
In this brief, a novel impulsive control has been proposed for consensus problems of discrete-time multi-agent systems. Utilizing the Lyapunov technique, a parametric discrete-time Riccati equation has been obtained i...
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ISBN:
(纸本)9781509035502
In this brief, a novel impulsive control has been proposed for consensus problems of discrete-time multi-agent systems. Utilizing the Lyapunov technique, a parametric discrete-time Riccati equation has been obtained in order to design impulsive controller. The derived criteria show that such impulsive control relies on the proper value of designed parameters and the upper bound of impulsive intervals. Finally, the applicability of proposed strategy is given through a numerical example.
In reality, traditional process control system built upon centralized and hierarchical structures presents a weak response to change and is easy to shut down by single failure. Aiming at these problems, a new agent-ba...
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In reality, traditional process control system built upon centralized and hierarchical structures presents a weak response to change and is easy to shut down by single failure. Aiming at these problems, a new agent-based service-oriented integration architecture was proposed for chemical process automation system. Web services were dynamically orchestrated on the internet and agent behaviors were built in them. Data analysis, model, optimization, control, fault diagnosis and so on were capsuled into different web services. Agents were used for service compositions by negotiation. A prototype system of poly(ethylene terephthalate) process automation was used as the case study to demonstrate the validation of the integration.
Until now, the canonical correlation analysis (CCA)-based method has been most widely applied to steady-state visual evoked potential (SSVEP). Artificial sine-cosine signals are used as the original references in the ...
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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.
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.
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