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第23届过程控制会议

作者： Xingdi Yan Wen Yang Hehe Ma Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education

The ammonia synthesis section is the core during the whole ammonia synthesis production. The ammonia concentration at the ammonia converter outlet is a significant process variable, which reflects the production efficiency directly. However, it is hard to be measured reliably online in real applications. In this paper, a soft sensor based on BP neural network (BPNN) is applied to estimate the ammonia concentration. A modified group search optimization with nearest neighborhood (GSO-NH) is proposed to optimize the weights and thresholds of BPNN. GSO-NH is integrated with BPNN to build a soft sensor model. Finally, the soft sensor model based on BPNN and GSO-NH (GSO-NH-NN) is used to infer the outlet ammonia concentration in a real-world application. Three other modeling methods are applied to compare with GSO-NH-NN. The results show that the soft sensor based on GSO-NH-NN has a good prediction performance with high accuracy. Moreover, the GSO-NH-NN also provides good generalization ability to other modeling problems in ammonia synthesis production.

关键词： Ammonia synthesis Ammonia concentration Soft sensor Group search optimization.

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The optimal model reduction method for spatially distributed system based on simulated annealing algorithm

The optimal model reduction method for spatially distributed...

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2012 International Conference on Computer Science and Information processing, CSIP 2012

作者： Wang, Mengling Shi, Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology 130 Meilong Road Shanghai 200237 China

ISBN: (纸本)9781467314114

For partial differential equation description unknown spatially distributed systems, the number of local models determines the dimension of the model. So far, there is no mature method about how to obtain the optimal region division. Usually, the local region division is related with the location of sensors. It may affect the accuracy and computational complexityH of the modeling directly. This paper presents an optimal model reduction approach for spatially distributed systems based on simulated annealing algorithm. At first, the optimality criterion is presented. And then, the simulated annealing based iterative optimizing method is proposed to solve the optimal model reduction. The simulations demonstrated show the accuracy and efficiency of the proposed methodologies. © 2012 IEEE.

关键词： Simulated annealing

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Event-triggered feedback control for piecewise-affine systems via convex combination 4

Event-triggered feedback control for piecewise-affine system...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Ma, Yifei Wu, Wei Cui, Baotong Ministry of Education Key Laboratory of Advanced Process Control for Light Industry Jiangnan University Wu Xi China

ISBN: (纸本)9781538683392

The problem of event-triggered control for discretetime piecewise-affine system with convex combination is investigated. The condition of asymptotic stability is proposed in the form of linear matrix inequalities (LMIs). The state-feedback control gain under the event-triggered strategy can be obtained by solving the LMIs. Subsequently, an optimization problem for minimizing the upper bound of quadratic cost function for quantifying the control performance are formulated. Unique state-feedback control gain under the event-triggering strategy can be obtained by solving the LMIs optimization problem. The effectiveness of our approach is illustrated by simulations of numerical example, where the number of control input updates is reduced, while the control performance is still guaranteed. © 2018 IEEE.

关键词： Linear matrix inequalities

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Improved Garson Algorithm based on Neural Network Model 29

Improved Garson Algorithm based on Neural Network Model

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第29届中国控制与决策会议

作者： Sun Maozhun Liu Ji Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology School of Information Science and Engineering East China University of Science and Technology

ISBN: (纸本)9781509046584

The evaluation of input factors of complex system is a hot and difficult point in the sensitivity analysis. In this paper, the Garson algorithm based on artificial intelligence is studied and the original Garson algorithm accuracy is not high. Therefore, an improved Garson algorithm is proposed and the input factors are introduced into the Garson algorithm. At the same time, the original local sensitivity analysis algorithm is improved as the global sensitivity analysis algorithm and it increases the accuracy and stability of the Garson algorithm. Through the typical benchmark test function simulation, the experimental results show that the improved Garson algorithm has higher accuracy and stability in the evaluation of sensitivity coefficient. Finally, the improved Garson algorithm is applied to evaluate the input factors of the plate-fin heat exchangers. It shows that the IGarson algorithm is more feasibility and effectiveness.

关键词： sensitivity analysis artificial intelligence neural network local sensitivity analysis global sensitivity analysis

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Iterative Learning Fault-tolerant control for Uncertain Batch process with Actuator Fault 10

Iterative Learning Fault-tolerant Control for Uncertain Batc...

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10th IEEE Data Driven control and Learning Systems Conference, DDCLS 2021

作者： Wang, Lei Yang, Huizhong Tao, Hongfeng Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214105 China

ISBN: (纸本)9781665424233

A closed-loop iterative learning fault-tolerant control scheme is proposed for batch process with actuator faults, in which the system parameters have uncertainties simultaneously. Firstly, the batch fault-tolerant controller is designed based on the two-dimensional (2D) system theory, and the batch process of iterative learning control is transformed to an equivalent 2D Roesser model. Then the sufficient conditions for the existence of the controller are analyzed in terms of linear matrix inequality (LMI) technique, and the control gain matrices are derived from the convex optimization problems with LMI constrains. Under these conditions of all additive uncertainties on system parameters and admissible failure, the proposed controller can ensure the closed-loop fault-tolerant performance along time. Finally, the simulation on injection molding nozzle pressure control simulation indicate that the proposed method achieve the design objective well, and show excellent fault tolerance performance. © 2021 IEEE.

关键词： Linear matrix inequalities

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Robust H∞ control for uncertain discrete networked control systems

Robust H∞ control for uncertain discrete networked control ...

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2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013

作者： Chen, Long Qu, Bai Da Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi 214122 China

ISBN: (纸本)9783037858202

This study is concerned with the robust H∞ control for a class of uncertain discrete Networked control Systems (NCSs). The NCSs with bounded network-induced delay and data packet dropout are modeled as closed-loop systems with time-varying input delay. By using new Lyapunov-Krasovskii function and combining Jessen inequality and reciprocal convex technique, a sufficient condition which asymptotically robust stabilizes closed-loop systems and satisfies H∞ performance index is derived. This study needs fewer Linear Matrix Inequality(LMI), compared with the existing literature. Therefore, the result obtains lower conservativeness. Finally, the robust H∞ controller is obtained with an improved cone complementarity linearization (ICCL).Simulation results show the effectiveness of the proposed method. © (2013) Trans Tech Publications, Switzerland.

关键词： Linear matrix inequalities

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Constrained optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： optimization algorithms

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PDBSCAN: Parallel DBSCAN for Large-Scale Clustering Applications

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Journal of Donghua University(English Edition) 2012年第1期29卷 76-79页

作者：谢永红马延辉周芳刘颖安 School of Computer and Communication Engineering University of Science and Technology Beijing Key Laboratory for Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing

Density-based algorithm for discovering clusters in large spatial databases with noise(DBSCAN) is a classic kind of density-based spatial clustering algorithm and is widely applied in several aspects due to good performance in capturing arbitrary shapes and detecting outliers. However, in practice, datasets are always too massive to fit the serial DBSCAN. And a new parallel algorithm-Parallel DBSCAN(PDBSCAN) was proposed to solve the problem which DBSCAN faced. The proposed parallel algorithm bases on MapReduce mechanism. The usage of parallel mechanism in the algorithm focuses on region query and candidate queue processing which needed substantive computation resources. As a result, PDBSCAN is scalable for large-scale dataset clustering and is extremely suitable for applications in E-Commence, especially for recommendation.

关键词： parallel DBSCAN clustering MapReduce large-scale applications

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Design of a Wireless Sensor Network node based on nRF2401

Design of a Wireless Sensor Network node based on nRF2401

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2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011

作者： Zhu, Jian-Hong Wang, Jun Liu, Di Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi 214122 China

ISBN: (纸本)9781424487257

As an important unit composing Wireless Sensor Networks, sensor node normally integrates sensor, data processing unit and communicating module. Power consuming and data transmitting rate are the key factors affecting the quality of it. Regarding the characteristics mentioned, we designed a new wireless sensor network node based on nRF2401. Since the node using low power consumption processor ATmega88 and wireless communication module nRF2401, it guarantees the system operating life and data transmission speed efficiently. Furthermore, the digital thermometer DS18B20 based on 1-wire technology can give the system more concision and more reliability. This node easily applies to Wireless Sensor Networks widely, with its characteristics of low-power, miniaturization and high integration. © 2011 IEEE.

关键词： Low power electronics

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Estimation of catalytic activity using an unscented Kalman filtering in condensation reaction

Estimation of catalytic activity using an unscented Kalman f...

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作者： Cang, Wentao Yang, Huizhong Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi214122 China

The catalytic activity of cation exchange resins will be continuously reduced with its use time in a condensation reaction for bisphenol A (BPA). For online estimation of the catalytic activity, a catalytic deactivation model is studied for a production plant of BPA, state equation and observation equation are proposed based on the axial temperature distribution of the reactor and the acetone concentration at reactor entrance. A hybrid model of state equation is constructed for improving estimation precision. The unknown parameters in observation equation are calculated with sample data. The unscented Kalman filtering algorithm is then used for on-line estimation of the catalytic activity. The simulation results show that this hybrid model has higher estimation accuracy than the mechanism model and the model is effective for production process of BPA. © 2015 Elsevier B.V.

关键词： Catalyst activity

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