This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination ...
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This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.
To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individua...
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To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. Differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.
Simultaneous saccharification and fermentation (SSF) of glutinous rice was performed by using o-amylase, glucoamylase, and rice wine yeast strain Saccharomyces cerevisiae Su-25. Experiments were carried out at two dif...
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ISBN:
(纸本)9781632668455
Simultaneous saccharification and fermentation (SSF) of glutinous rice was performed by using o-amylase, glucoamylase, and rice wine yeast strain Saccharomyces cerevisiae Su-25. Experiments were carried out at two different locations, and the main products were identified and measured by HPLC. A low-order kinetic model structure (forms or constructs of model with adjustable parameters) was proposed based on the major chemical reactions in the SSF process. The model structure was then tested for its abilities to capture the main kinetic variations after parameter optimization by a least-squares algorithm. The proposed model structure was found useful in representing measured kinetic variations. The estimated reactions rates correctly reflected the variations observed from the experiments and provided insights into the reaction processes. While additional research is warranted for further validation and refinement, the proposed model structure shows promise for describing the simultaneous saccharification and fermentation process of glutinous rice.
This paper studies a synthesis approach to predictive control for networked control systems with data loss and quantization. An augmented Markov jump linear model with polytopic uncertainties is modeled to describe th...
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ISBN:
(纸本)9781479947249
This paper studies a synthesis approach to predictive control for networked control systems with data loss and quantization. An augmented Markov jump linear model with polytopic uncertainties is modeled to describe the quantization errors and possible data loss. Based on this model, a predictive control synthesis approach is developed, which involves online optimization of a infinite horizon objective and conditions to deal with system constraints. The proposed MPC algorithm guarantees closed-loop mean-square stability and constraints satisfaction.
This paper focuses on the problem of cluster synchronization of a class of complex dynamical *** on impulsive control theory and a comparison theorem, generic criteria for cluster synchronization are derived. It is sh...
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This paper focuses on the problem of cluster synchronization of a class of complex dynamical *** on impulsive control theory and a comparison theorem, generic criteria for cluster synchronization are derived. It is shown that these criteria provide a novel and effective control approach to synchronize a general dynamical network to a cluster synchronization manifold by exposing the relationship between cluster synchronization, the impulsive intervals,and the graph topology.
In this paper, a linear unbiased minimum-variance filtering problem is considered for a class of systems with randomly multi-step sensor delays. A new mathematical model is established for the multi-step sensor delays...
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ISBN:
(纸本)9781479940318
In this paper, a linear unbiased minimum-variance filtering problem is considered for a class of systems with randomly multi-step sensor delays. A new mathematical model is established for the multi-step sensor delays. Different from the augmented method for dealing with delayed systems, a linear unbiased minimum-variance filter design method is proposed without augmenting the state vector, which effectively reduces the filter dimensions. A recursive algorithm for calculating the filter gain matrix is developed. The simulation results illustrate the effectiveness of the proposed method.
This paper considers distributed estimation over heterogeneous sensor networks. We propose a distributed estimation strategy based on PageRank algorithm, where the link weight depends on the edge estimation covariance...
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This paper considers the distributed estimation of an unstable target via constant-gain estimators under local communications and channel fading. The communication graph is assumed to be fixed and undirected, and the ...
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This paper considers the distributed estimation of an unstable target via constant-gain estimators under local communications and channel fading. The communication graph is assumed to be fixed and undirected, and the channel fading is assumed to be identical. Necessary and sufficient conditions on communication network over which the state of the unstable target can be estimated in the mean square sense are given for both continuous-time and discrete-time cases, which reveal the fundamental limitation on distributed estimation induced by local communications, channel fading, and target dynamics. In addition, our results for the case without channel fading and the case with separate communications are consistent with the results in the literature.
The proper control of the ratio of ore to coke distribution(ROCD) can achieve energy saving of the blast furnace(BF).In order to achieve the desired ROCD,it is meaningful to search best charging system(especially the ...
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ISBN:
(纸本)9781479947249
The proper control of the ratio of ore to coke distribution(ROCD) can achieve energy saving of the blast furnace(BF).In order to achieve the desired ROCD,it is meaningful to search best charging system(especially the burden matrix).This paper deals with the problem of burden distribution control based on the adaptive genetic algorithm and multi-radar ***,the definition of the ratio of ore to coke(ROC) and the desired ROCD are ***,according to the desired ROCD,the concrete steps of searching the best burden matrices are presented based on the adaptive genetic ***,the operators of the adaptive genetic algorithm(especially the mutation operator) are properly adjusted,according to the actual production process of the bell-less ***,three computational experiments demonstrate the effectiveness of the method.
This paper analyses the application status of cloud services to identify four factors that affect the security of enterprise cloud services (ECSs), including platform facilities, operational safety, operations managem...
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This paper analyses the application status of cloud services to identify four factors that affect the security of enterprise cloud services (ECSs), including platform facilities, operational safety, operations management, and legal factors. Based on the four factors, the grey fuzzy analytic hierarchy process (GFAHP) is used to construct an evaluation model for the security of ECSs. An example is investigated to demonstrate the proposed model.
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