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Balanced multiple weighted linear discriminant analysis and its application to visual process monitoring

Chinese Journal of chemical Engineering 2021年第8期34卷 128-137页

作者： Weipeng Lu Xuefeng Yan Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and TechnologyShanghai 200237China

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.

关键词： Linear discriminant analysis process monitoring Self-organizing map Feature extraction Continuous stirred tank reactor process

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Biogeography-based multi-objective optimization algorithm with hybrid migration and applying in ethylene cracking process 36

Biogeography-based multi-objective optimization algorithm wi...

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第36届中国控制会议

作者： Zheming Huang Rongbin Qi East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical ProcessMinistry of Education

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.

关键词： biogeography-based optimization multi-objective self-adaptive migration ethylene cracking optimization

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Improved Estimation of Distribution Algorithm for Solving Unrelated Parallel Machine Scheduling Problem

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Journal of Donghua University(English Edition) 2016年第5期33卷 797-802页

作者：孙泽文顾幸生 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

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.

关键词： Scheduling neighborhood scheduling minimizing processed unrelated probabilistic intelligent heuristic representing

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Robust Tracking control of Nonlinear Singularly Perturbed Systems 36

Robust Tracking Control of Nonlinear Singularly Perturbed Sy...

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第36届中国控制会议

作者： Jing Xu Yugang Niu the Key Laboratory of Advanced Control and Optimization for Chemical Process （East China University of Science and Technology） Ministry of Education

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.

关键词： Self-scheduled Tracking control Singularly perturbed systems Robust control

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Exponential dissipative control of stochastic systems under wireless communication networks 35

Exponential dissipative control of stochastic systems under ...

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第35届中国控制会议

作者： SONG Jun NIU Yugang ZOU Yuanyuan Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education

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.

关键词： Stochastic systems fading channel dissipative control

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Convergence Analysis for an Identifier-Based Adaptive Dynamic Programming Algorithm 34

Convergence Analysis for an Identifier-Based Adaptive Dynami...

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第三十四届中国控制会议

作者： SONG Jun NIU Yugang ZOU Yuanyuan Key Laboratory of Advanced Control and Optimization for Chemical Process (East China University of Science and Technology) Ministry of Education

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.

关键词： Adaptive Dynamic Programming(ADP),Markov Jump Systems(MJSs),Uniformly Ultimately Boundedness(UUB)

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Simultaneous hydrogen production with photo reforming of lactic acid over MXene derived MoS_(2)/TiO_(2)/Ti_(3)C_(2)nanowires

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Chinese Journal of Catalysis 2025年第4期71卷 234-245页

作者： Seemal Mansoor Zixu Hu Yuxin Zhang Muhammad Tayyab Mazhar Khan Zeeshan Akmal Liang Zhou Juying Lei Muhammad Nasir Jinlong Zhang Key Laboratory for Advanced Materials Shanghai Engineering Research Center for Multi–media Environmental Catalysis and Resource UtilizationJoint International Research Laboratory of Precision Chemistry and Molecular EngineeringFeringa Nobel Prize Scientist Joint Research CenterSchool of Chemistry and Molecular EngineeringEast China University of Science&TechnologyShanghai 200237China National Engineering Research Center of Industrial Wastewater Detoxication and Resource Recovery State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical ProcessEast China University of Science and TechnologyShanghai 200237China State Key Laboratory of Urban Water Resource and Environment Harbin Institute of TechnologyHarbin 150090HeilongjiangChina Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055GuangdongChina COMSATS Univ Islamabad Interdisciplinary Res Ctr Biomed Mat IRCBMLahore CampusLahore 54000Pakistan

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.

关键词： Photo reforming Polylactic acid Hydrogen evolution Lactic acid Pyruvic acid

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Dynamic Multi-objective optimization of chemical processes Using Modified BareBones MOPSO Algorithm

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Journal of Donghua University(English Edition) 2014年第2期31卷 184-189页

作者：杜文莉王珊珊陈旭钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

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 chemical processes. 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.

关键词： dynamic multi-objective optimization bare-bones particle swarm optimization(PSO) algorithm chemical process

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On-Line Batch process Monitoring Using Multiway Kernel Partial Least Squares

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Journal of Donghua University(English Edition) 2011年第6期28卷 585-590页

作者：胡益马贺贺侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

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.

关键词： process monitoring fault detection kernel partial least squares(KPLS) nonlinear process multiway kernel partial least squares(MKPLS)

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Locust Behaved Particle Swarm optimization Technique

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Journal of Donghua University(English Edition) 2014年第2期31卷 190-196页

作者：钟伟民谢雪勤梁毅罗娜张娟钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

The collective behavior of certain animals and insects has the characteristic of self-organization. The simple interactions among individuals can produce complex adaptive patterns at the level of the group. Recently,new scientific investigation pointed out that desert locusts show extreme phenotypic plasticity in transforming between the lonely phase and the swarming gregarious phase depending on the population density,which is controlled by a serotonin called 5-hydroxytryptamine( 5HT). In this paper,based on the mechanism of the locusts' collective behavior,a new particle swarm optimization technique called LBPSO is studied. The number of swarms is selfadaptively adjusted by the acquired outstanding particles coming from behind the previous global best solution. The swarm sizes are related to the corresponding serotonin 5HT,which is determined by the optimization parameters such as global best and iteration number. And each swarm adopts one of three rules below according to its density, generalized social evolution strategy, generalized cognition evolution strategy and the independent moving strategy. A comparative study of LBPSO,social particle swarm optimization( SPSO), improved SPSO and the standard particle swarm optimization( StdPSO) on their abilities of tracking optima is carried out. And the results under four static benchmark functions and a dynamic function generator moving peaks benchmark( MPB)show that LBPSO outperforms the other three functions in both static and dynamic landscapes due to the introduced locusts' collective behavior.

关键词： evolutionary algorithm particle swarm optimization(PSO) locust collective behavior

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