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A new improved Alopex-based evolutionary algorithm and its application to parameter estimation

Journal of Central South University 2013年第1期20卷 123-133页

作者：桑志祥李绍军董跃华 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

In this work, focusing on the demerit of AEA (Alopex-based evolutionary algorithm) algorithm, an improved AEA algorithm (AEA-C) which was fused AEA with clonal selection algorithm was proposed. Considering the irrationality of the method that generated candidate solutions at each iteration of AEA, clonal selection algorithm could be applied to improve the method. The performance of the proposed new algorithm was studied by using 22 benchmark functions and was compared with original AEA given the same conditions. The experimental results show that the AEA-C clearly outperforms the original AEA for almost all the 22 benchmark functions with 10, 30, 50 dimensions in success rates, solution quality and stability. Furthermore, AEA-C was applied to estimate 6 kinetics parameters of the fermentation dynamics models. The standard deviation of the objective function calculated by the AEA-C is 41.46 and is far less than that of other literatures' results, and the fitting curves obtained by AEA-C are more in line with the actual fermentation process curves.

关键词： Alopex evolutionary algorithm Alopex-based evolutionary algorithm clone selection parameter estimation

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chemical process dynamic optimization based on hybrid differential evolution algorithm integrated with Alopex

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Journal of Central South University 2013年第4期20卷 950-959页

作者：范勤勤吕照民颜学峰郭美锦 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

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.

关键词： evolutionary computation dynamic optimization differential evolution algorithm Alopex algorithm self-adaptivity

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Adaptive neural control for pure-feedback nonlinear time-delay systems with unknown dead-zone: a Lyapunov-Razumikhin method

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控制理论与应用（英文版） 2013年第1期11卷 18-26页

作者： Zhaoxu YU Jianxu LUO Ji LIU Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

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.

关键词： Pure-feedback nonlinear systems Adaptive neural control Razumikhin functional Time-delay Deadzone

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Coupling pinch analysis and rigorous process simulation for hydrogen networks with light hydrocarbon recovery

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Chinese Journal of chemical Engineering 2021年第12期34卷 141-148页

作者： Minbo Yang Xiao Feng Liang Zhao Shaanxi Key Laboratory of Energy Chemical Process Intensification School of Chemical Engineering and TechnologyXi’an Jiaotong UniversityXi'an 710049China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of EducationShanghai 200237China

In refineries,some hydrogen-rich streams contain considerable light hydrocarbons that are important raw materials for the chemical *** hydrogen networks with light hydrocarbon recovery can enhance the reuse of both hydrogen and light *** work proposes an automated method for targeting hydrogen networks with light hydrocarbon recovery.A pinch-based algebraic method is improved to determine the minimum fresh hydrogen consumption and hydrogen sources fed into the light hydrocarbon recovery unit *** process simulation is conducted to determine the mass and energy balances of the light hydrocarbon recovery *** targeting procedures are developed through combination of the improved pinch method and rigorous process *** hybrid method is realized by coupling the Matlab and Aspen HYSYS platforms.A refinery hydrogen network is analyzed to illustrate application of the proposed *** integration of hydrogen network with light hydrocarbon recovery further reduces fresh hydrogen requirement by463.0 m^(3)·h^(-1) and recovers liquefied petroleum gas and gasoline of 1711.5 kg·h^(-1) and 643 kg·h^(-1),respectively.A payback period of 9.2 months indicates that investment in light hydrocarbon recovery is economically attractive.

关键词： Hydrogen Light hydrocarbon recovery Pinch technology Simulation Systems engineering

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Global output feedback adaptive stabilization for systems with long uncertain input delay

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Science China(Information Sciences) 2023年第1期66卷 326-327页

作者： Zhuping WANG Jingcheng LIU Chao HUANG Hao ZHANG Huaicheng YAN School of Electronics and Information Engineering Tongji University Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology

Dear editor,The uncertain input delay is frequently encountered in engineering control systems. Adaptation is indispensable when the uncertain input delay is significant. In existing delayadaptive controllers [1–6], the actuator state must be measured to achieve global stability. Recently, a logic-based switching delay-adaptive state-feedback controller [7] was proposed to realize global stability without measuring the actuator state.

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Multimodal process monitoring based on transition-constrained Gaussian mixture model

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Chinese Journal of chemical Engineering 2020年第12期28卷 3070-3078页

作者： Shutian Chen Qingchao Jiang Xuefeng Yan Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and TechnologyShanghai 200237China

Reliable process monitoring is important for ensuring process safety and product quality.A production process is generally characterized bymultiple operation modes,and monitoring thesemultimodal processes is *** multimodal monitoring methods rely on the assumption that the modes are independent of each other,which may not be appropriate for practical *** study proposes a transition-constrained Gaussian mixture model method for efficient multimodal process *** technique can reduce falsely and frequently occurring mode transitions by considering the time series information in the mode identification of historical and online *** process enables the identified modes to reflect the stability of actual working conditions,improve mode identification accuracy,and enhance monitoring reliability in cases of mode *** studies on a numerical simulation example and simulation of the penicillin fermentation process are provided to verify the effectiveness of the proposed approach inmultimodal process monitoring with mode overlap.

关键词： Multimodal process monitoring Gaussian mixture model State transition matrix process control process systems Systems engineering

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A novel chemical composition estimation model for cement raw material blending process

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Chinese Journal of chemical Engineering 2019年第11期27卷 2734-2741页

作者： Yaoyao Bao Yuanming Zhu Weimin Zhong Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and TechnologyShanghai 200237China

Raw material blending process is an essential part of the cement production process. The main purpose of the process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating the four raw materials. But the chemical compositions of raw materials vary from time to time, resulting in difficulties to control the oxide compositions to a predefined value. Therefore, a novel algorithm to estimate the chemical compositions of the raw materials is developed. The paper mainly consists of two parts. In model construction part, a novel constrained least square model is proposed to overcome the deviation introduced by long-term drift of the material components, and the model parameters are estimated with an online strategy. And in validation part, the approach is implemented to two examples including datasets from simulation model and the actual industrial process. The final results show the effectiveness of the proposed method.

关键词： Raw material blending process chemical component estimation Modulus prediction System identification

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A subspace ensemble regression model based slow feature for soft sensing application

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Chinese Journal of chemical Engineering 2020年第12期28卷 3061-3069页

作者： Qiong Jia Jun Cai Xinyi Jiang Shaojun Li Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of EducationShanghai 200237China

A novel adaptive subspace ensemble slow feature regression model was developed for soft sensing *** to traditional single models and random subspace models,the proposed method is improved in three ***,sub-datasets are constructed through slow feature directions and variables in each subdatasets are selected according to the output related importance ***,an adaptive slow feature regression is presented for ***,a Bayesian inference strategy based on a slow feature analysis process that monitors statistics is developed for probabilistic *** industrial examples were used to evaluate the proposed method.

关键词： Soft sensing Slow feature regression Subspace modeling Ensemble learning

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Exploring Si/Mg Composite Supported Ziegler-Natta Ti-based Catalysts for Propylene Polymerization

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Chinese Journal of Polymer Science 2017年第12期35卷 1474-1487页

作者： Wei Zhu 田洲 Rui-hua Cheng Xue-lian He Zhen Liu Ning Zhao 刘柏平 State Key Laboratory of Chemical Engineering East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

A series of（SiO2/MgO/ID/MgCl2）·TiClx Ziegler-Natta catalysts for propylene polymerization has been prepared with a new method. These catalysts were synthesized using soluble Mg-compounds as the Mg-source and the preparation progress was relatively simple. The catalyst could copy the spherical shape of the carrier very well. The propylene polymerization results showed that the catalyst revealed the best activity with 9,9-di（methoxymethyl）fluorene（BMMF） as internal donor at 50 °C with the optimal molar ratio Al/Ti = 5, which was much lower than what the industrial polypropylene catalyst used（at least molar ratio Al/Ti = 100）, resulting in great cost saving. Additionally, the polymerization kinetics of the catalyst exhibited very stable property after achieving a relatively high value. These catalysts possessed rather high activity and good hydrogen response. The isotactic index（Ⅱ.） value of the PP products could be higher than 98% in the presence of both internal and external electron donors. Moreover, temperature rising elution fractionation method was used to understand the influence of donors and H2 on the properties of the PP products.

关键词： Polypropylene Ziegler-Natta catalyst External donor Intemal donor Kinetic curves

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Multi-mode process monitoring based on a novel weighted local standardization strategy and support vector data description

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Journal of Central South University 2016年第11期23卷 2896-2905页

作者：赵付洲宋冰侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education(East China University of Science and Technology) Shanghai 200237China

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.

关键词： multiple operating modes weighted local standardization support vector data description multi-mode monitoring

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