Visual process monitoring is important in complex chemical *** address the high state separation of industrial data,we propose a new criterion for feature extraction called balanced multiple weighted linear discrimina...
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Visual process monitoring is important in complex chemical *** address the high state separation of industrial data,we propose a new criterion for feature extraction called balanced multiple weighted linear discriminant analysis(BMWLDA).Then,we combine BMWLDA with self-organizing map(SOM)for visual monitoring of industrial operation *** can extract the discriminative feature vectors from the original industrial data and maximally separate industrial operation states in the space spanned by these discriminative feature *** the discriminative feature vectors are used as the input to SOM,the training result of SOM can differentiate industrial operation states *** function improves the performance of visual *** stirred tank reactor is used to verify that the class separation performance of BMWLDA is more effective than that of traditional linear discriminant analysis,approximate pairwise accuracy criterion,max–min distance analysis,maximum margin criterion,and local Fisher discriminant *** addition,the method that combines BMWLDA with SOM can effectively perform visual process monitoring in real time.
There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because the...
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There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.
The Ethylene cracking is highly nonlinear, complex process with many constraints because of the complex running state of cracking furnace groups. For the solutions to multi-objective problems of yield, cost and benefi...
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ISBN:
(纸本)9781538629185
The Ethylene cracking is highly nonlinear, complex process with many constraints because of the complex running state of cracking furnace groups. For the solutions to multi-objective problems of yield, cost and benefits, this paper puts forward a biogeography-based multi-objective optimization algorithm with hybrid migration（BBMOHM）. The hybrid migration strategy combines the self-adaptive migration with the simplex operator and the replication migration, which strengthens the convergence and the search ability, to avoid falling into local optimum. For the goal of utilizing the dominance information between individuals, this algorithm adopts the migration model of dominance degree to assist migration strategies improving the performance of the algorithm. Finally, experiments about the ZDT test function and the multi-objective optimization problem of the ethylene cracking process is verified the BBMOHM achieves good performance on convergence and distribution.
Scheduling problem is a well-known combinatorial optimization *** effective improved estimation of distribution algorithm(IEDA) was proposed for minimizing the makespan of the unrelated parallel machine scheduling pro...
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Scheduling problem is a well-known combinatorial optimization *** effective improved estimation of distribution algorithm(IEDA) was proposed for minimizing the makespan of the unrelated parallel machine scheduling problem(UPMSP).Mathematical description was given for the *** IEDA which was combined with variable neighborhood search(IEDA_VNS) was proposed to solve the UPMSP in order to improve local search ability.A new encoding method was designed for representing the feasible solutions of the *** knowledge of the UPMSP were taken consideration in IEDA_ VNS for probability matrix which was based the processing time *** simulation results show that the proposed IEDA_VNS can solve the problem effectively.
This paper presents a robust control scheme for the tracking control of singularly perturbed uncertain systems. The design problem is divided into two parts: tracking the reference trajectory and enhancing the robustn...
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ISBN:
(纸本)9781538629185
This paper presents a robust control scheme for the tracking control of singularly perturbed uncertain systems. The design problem is divided into two parts: tracking the reference trajectory and enhancing the robustness of the dynamic *** using the time-scale techniques, dynamic inversion approach and linear parameter-varying methods, a set of singularly perturbed state feedback controllers are employed to enhance the tracking performance and robustness of a dynamic system against parameter uncertainties, actuator and sensor unmodelled dynamics, and external disturbances. The longitudinal control of an F16 aircraft model is included to show the merits and and effectiveness of the proposed design scheme.
In this work,the problem of dissipative control is investigated for stochastic systems under the unreliable wireless network,in which there may exist stochastic fading ***,a modified Rice fading model with disturbance...
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ISBN:
(纸本)9781509009107
In this work,the problem of dissipative control is investigated for stochastic systems under the unreliable wireless network,in which there may exist stochastic fading ***,a modified Rice fading model with disturbance-dependent noise is *** then,a state-feedback controller with fading measurements is designed and the some sufficient conditions are derived such that the closed-loop system is finite-time stochastic bounded with a prescribed exponentially dissipative ***,numerical simulation results are provided.
This paper investigates the uniformly ultimate boundedness(UUB) of an identifier-based adaptive dynamic programming(ADP) algorithm proposed in [7]. It is demonstrated that the estimation errors of weights in both crit...
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ISBN:
(纸本)9781467374439
This paper investigates the uniformly ultimate boundedness(UUB) of an identifier-based adaptive dynamic programming(ADP) algorithm proposed in [7]. It is demonstrated that the estimation errors of weights in both critic and action networks are UUB during iteration learning. Moreover, a selection method on learning rates is also given.
Developing efficient photocatalysts to address collaborative energy and environmental crises still faces significant *** this report,we present a highly efficient MXene–based photocatalyst,which is combined with MoS_...
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Developing efficient photocatalysts to address collaborative energy and environmental crises still faces significant *** this report,we present a highly efficient MXene–based photocatalyst,which is combined with MoS_(2)nano patches and TiO_(2)/Ti_(3)C_(2)(TTC)nanowires through hydrothermal *** all the composites tested,the optimized photocatalyst gave a remarkable H_(2)and revolving polylactic acid(PLA)into pyruvic acid(PA).Achieving a remarkable H_(2)evolution rate of 637.1 and 243.2μmol g^(−1)h^(−1),in the presence of TEOA and PLA as a sacrificial reagent under UV-vis(λ≥365 nm)light *** improved photocatalytic activity is a result of the combination of dual cocatalyst on the surface of TTC photocatalyst,which create an ideal synergistic effect for the generation of PA and the production of H_(2)*** MoS_(2)TiO_(2)/Ti_(3)C_(2)(MTT)composite can generate more photoexcited charge carriers,leading to the generation of more active radicals,which may enhance the system's photocatalytic *** work aims at demonstrating its future significance and guide the scientific community towards a more efficient approach to commercializing H_(2)through photocatalysis.
Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering. In this paper,a modified multi-objective bare-bones particle swarm optimization( MOBBPSO) algorithm is pro...
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Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering. In this paper,a modified multi-objective bare-bones particle swarm optimization( MOBBPSO) algorithm is proposed that takes advantage of a few parameters of bare-bones algorithm. To avoid premature convergence,Gaussian mutation is introduced; and an adaptive sampling distribution strategy is also used to improve the exploratory capability. Moreover, a circular crowded sorting approach is adopted to improve the uniformity of the population ***, by combining the algorithm with control vector parameterization,an approach is proposed to solve the dynamic optimization problems of chemicalprocesses. It is proved that the new algorithm performs better compared with other classic multiobjective optimization algorithms through the results of solving three dynamic optimization problems.
An approach for batch processes monitoring and fault detection based on multiway kernel partial least squares(MKPLS) was *** is known that conventional batch process monitoring methods,such as multiway partial least s...
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An approach for batch processes monitoring and fault detection based on multiway kernel partial least squares(MKPLS) was *** is known that conventional batch process monitoring methods,such as multiway partial least squares(MPLS),are not suitable due to their intrinsic linearity when the variations are *** address this issue,kernel partial least squares(KPLS) was used to capture the nonlinear relationship between the latent structures and predictive *** addition,KPLS requires only linear algebra and does not involve any nonlinear *** this paper,the application of KPLS was extended to on-line monitoring of batch *** proposed batch monitoring method was applied to a simulation benchmark of fed-batch penicillin fermentation *** the results demonstrate the superior monitoring performance of MKPLS in comparison to MPLS monitoring.
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