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Asian control Conference

作者： Jing Xu Yugang Niu The Key Laboratory of Advanced Control and Optimization for Chemical Process East China University of Science and Technology

ISBN: (纸本)9781728102634

Based on the switching strategy, this paper presents an finite frequency formulation for the robust stabilization of singularly perturbed uncertain systems. An uncertain system is modeled as a parallel connection of a nominal system and an error system represented in the form of a linear parameter-varying system. A family of dynamic output feedback controllers are designed to enhance the robustness of the error system against finite frequency uncertainties over the operational region. A hysteresis switching is proposed to coordinate the candidate controllers. The proposed scheme is applied in the longitudinal control of an F16 aircraft to verify its effectiveness and merits.

关键词： Switches Frequency control Symmetric matrices Uncertain systems Uncertainty Actuators

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Estimation of distribution algorithm sampling under gaussian and cauchy distribution in continuous domain

Estimation of distribution algorithm sampling under gaussian...

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2010 8th IEEE International Conference on control and Automation, ICCA 2010

作者： Luo, Na Qian, Feng Automatic Institute Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai 200237 China State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 200237 China

ISBN: (纸本)9781424451951

Estimation of Distribution Algorithm is a new population based evolutionary optimization method and it generates new population from probability distribution model. Like most evolutionary algorithms, it is easy to trap into local optimums. In order to avoid this shortcoming, Gaussian and Cauchy probability density function are mixed as probability distribution model. For continuous problems, a new estimation of distribution algorithm sampling under the mixed model is presented. New individuals are generated not only from Gaussian distribution but sometimes from Cauchy distribution in order to keep diversity. The selection strategy of Gaussian and Cauchy distribution are also discussed. The new algorithm is tested on five benchmark functions and results are compared with basic and estimation of distribution algorithm with Cauchy mutation. © 2010 IEEE.

关键词： Gaussian distribution

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Linear parameter varying control of wind energy conversion systems in partial load 19

Linear parameter varying control of wind energy conversion s...

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19th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Xu, Jing Sun, Qing East China University of Science and Technology Ministry of Education The Key Laboratory of Advanced Control and Optimization for Chemical Process Shanghai200237 China Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronical Engineering and Automation Shanghai200072 China

ISBN: (纸本)9780738124261

This paper is dealt with the rotor speed tracking problem of variable-speed wind turbine systems operating under the partial load condition. Singular perturbation techniques are used to characterize the two-time-scale property of the wind turbine system, and a linear parameter varying (LPV) model is formed to approximate nonlinear behaviours of a wind turbine system. Based on the slow-fast decomposition method, slow and fast subsystems are constructed: one for the mechanical dynamics and the other for the electrical dynamics. Slow and fast controls are derived, respectively, and then a local state feedback controller, sum of the slow and fast control, is formulated. A design procedure, using the linear parameter varying control to combine local controllers, is proposed to guarantee the robustness of the closed-loop nonlinear wind turbine system. Numerical examples are given to show the validity of the proposed control scheme. © 2020 IEEE.

关键词： Wind turbines

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Gradient-based immune algorithm for optimization of dynamic environments

Gradient-based immune algorithm for optimization of dynamic ...

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International Conference on Natural Computation

作者： Shi, Xuhua Qian, Feng Research Institute of Electric Automatic Control NingBo University NingBo China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ecust China University of Science and Technology ShangHai China

ISBN: (纸本)9781424459612

A novel immune algorithm suitable for dynamic environments (GIDE) is proposed based on a biological immune mechanism. GIDE models the dynamic process of artificial immune response with gradient-based diversity operators. Unlike traditional artificial immune algorithms, which require that randomly generated cells be added to the current population to explore its fitness landscape, GIDE uses a gradient-based diversity operator to speed up optimization in dynamic environments. Other immune algorithms are compared to GIDE by using Moving Peaks Benchmarks. Preliminary experiments showed that GIDE can maintain high population diversity during the search process, while simultaneously speeding up optimization. Thus, GIDE is useful for optimization of dynamic environments. © 2010 IEEE.

关键词： Bioinformatics

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Soft sensor for ammonia concentration at the ammonia converter outlet based on an improved group search optimization and BP neural network

Soft sensor for ammonia concentration at the ammonia convert...

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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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Immune agent-based neural networks assembly for soft-sensor

Immune agent-based neural networks assembly for soft-sensor

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2nd International Workshop on Intelligent Systems and Applications, ISA2010

ISBN: (纸本)9781424458745

Aiming at difficulty modeling of large amounts of industrial process data, a novel soft sensor model based on artificial immune agent-based multiple model Radial Basis Function (RBF) networks is proposed in this paper. The method is to predict the qualities of manufactured products of Crude Oil Tower. In the IMMST-Team system, some biological immune based operation and learning rules which can efficiently cluster the large amounts of data samples and adapt RBF submodels structure and parameter are established. Individuals in the immune system work cooperatively to accomplish the goal of model training. Meenwhile, immune memory and pattern recognition provide high efficiency of predicting. The prediction of dry point of naphtha produced in a practical industrial process is carried out as a case study. The results obtained indicate that the proposed method provides quality prediction with high efficiency and accuracy, which is capable of learning the relationships between process variables measured during the production cycle. ©2010 IEEE.

关键词： Crude oil

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A Typical Power Allocation for Distributed Filtering

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IFAC-PapersOnLine 2017年第1期50卷 10550-10555页

作者： Zhang Y. Yang W. Yang C. Wang X. Sha F. Tian Y. Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 China Department of Automation Shanghai Jiaotong University Shanghai 200240 China

In this paper, the problem of power allocation is considered for distributed estimation over a sensor network with limited power. An online power allocation scheme is introduced to optimize the power consumption, where the power distributed to each communication channel depends on the innovation value of the sender. First, an optimal estimator gain is designed for each sensor by minimizing the mean-squared estimation error covariance. Second, a sufficient condition is provided to guarantee the stability of networked system with online power allocation scheme. Finally, we compare the estimation performance of the proposed online power scheduling scheme with some typical offline power scheduling schemes. © 2017

关键词： Distributed estimation Modified algebraic Riccati equation (MARE) Power allocation Transmission probability

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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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Oil extraction from sunflower seed using green solvent 22

Oil extraction from sunflower seed using green solvent

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22nd International Congress of chemical and process Engineering, CHISA 2016 and 19th Conference on process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction, PRES 2016

作者： De Jesus, S.S. Santana, A. Maciel Filho, R. Laboratory of Optimization Design and Advanced Control School of Chemical Engineering University of Campinas Campinas SP13083-970 Brazil Laboratory of High Pressure Process Department of Chemical Engineering and Environmental Technology University of Valladolid Valladolid47011 Spain

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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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