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第36届中国控制会议

作者： Yan Dong Zhaoxu Yu Fangfei Li Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Department of Mathematics East China University of Science and Technology

ISBN: (纸本)9781538629185

This paper focuses on the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown control coefficients and quantized input. The difficulty from the unknown control direction is solved by using the linear state transformation and the Nussbaum gain function（NGF） approach. Based on the combination of input-driven observer, backstepping technique, neural network（NN） parametrization and variable separation method, a novel adaptive output feedback quantized control scheme involving only one adaptive parameter is developed for such systems. The designed quantized controller ensures that all signals of closed-loop systems are semi-globally uniformly ultimately bounded（SGUUB）, and the tracking error converges to an adjustable neighborhood of the origin. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed control design.

关键词： Nonstrict-feedback systems quantized input signal output feedback adaptive control unknown control direction

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GPU-based coevolutionary particle swarm optimization 36

GPU-based coevolutionary particle swarm optimization

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第36届中国控制会议

作者： ZHAO Liang Zhu Yanxing ZHANG Jianyu Ye Zhencheng Key Laboratory of Advanced Control and Optimization for Chemical Process(Ministry of Education) East China University of Science and Technology Ethylene Plant of Jilin Petrochemical Company Ltd.PetroChina

ISBN: (纸本)9781538629185

Coevolutionary particle swarm optimization（CPSO） algorithm has been investigated and applied in the real world *** tackling the large-scale and complex real time optimization problems,the running time of CPSO algorithm is a *** this paper,Graphics Processing Unit（GPU） is introduced to provide speedup in order to meet the real time *** CPSO algorithm has been implemented on GPU concurrently using the CUDA *** performance and run time of CPU-based and GPU-based CPSO algorithms are compared in *** experiment result shows that the GPU-based parallel computation mode can shorten the run time of CPSO algorithm apparently.

关键词： GPU CUDA Particle swarm optimization Coevolutionary particle swarm optimization

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Initial-Parameter-Criterion based Gaussian Mixture Model Monitoring Method for Non-Gaussian Process

Initial-Parameter-Criterion based Gaussian Mixture Model Mon...

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第37届中国控制会议

作者： Ying Tian Wenli Du Shanghai Key Lab of Modern Optical System School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

Gaussian mixture model(GMM) monitoring method is commonly used for non-Gaussian process monitoring. In GMM monitoring method, the final number of Gaussian components and the statistical distribution parameters are estimated through the improved Figueiredo-Jain(F-J) algorithm in the modeling phase. However, the data dimensionality of modern industry is high, the number of initial Gaussian components is large for the accuracy of the algorithm. Under this condition, the relative small number of samplings makes the denominator in the weight estimation formula of the improved F-J algorithm become zero and the algorithm suspends. To make the algorithm work well in an acceptable modeling time, we deduce the Initial-ParameterCriterion among initial Gaussian components, data dimension, sampling number and propose the Initial-Parameter-Criterion based GMM(IPC-GMM) monitoring method. The proposed monitoring method is used for TE process monitoring, simulation results reveal the effectiveness and necessity of IPC-GMM monitoring method.

关键词： non-Gaussian process monitoring Gaussian mixture model Initial-Parameter-Criterion

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Finite time boundedness of switched delay systems by sliding mode technique 36

Finite time boundedness of switched delay systems by sliding...

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第36届中国控制会议

作者： Haijuan Zhao Yugang Niu Tinggang Jia Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education Automation Division of Shanghai Electric Group Co. Ltd.

ISBN: (纸本)9781538629185

In this paper,the finite-time boundedness（FTB） problem of sliding mode control（SMC） is investigated for a class of switched delay systems subject to uncertain parameter and nonlinear perturbation.A SMC law is constructed to drive the state trajectories onto the integral sliding surface during a finite time *** FTB of the controlled systems on both reaching phase and siding motion phase are analyzed by means of average dwell time ***,a numerical example is given.

关键词： Switched delay system Finite time boundedness Sliding mode control Average dwell time

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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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A Novel Improved Grey Wolf optimization Algorithm for Numerical optimization and PID controller Design

A Novel Improved Grey Wolf Optimization Algorithm for Numeri...

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Data Driven control and Learning Systems (DDCLS)

作者： Tao Zhang Xin Wang Zhenlei Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Center of Electrical & Electronic Technology Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781538626191

The grey wolf optimization (GWO) algorithm, one of the recently proposed bio-inspired algorithms, simulates the leadership hierarchy and hunting mechanism of grey wolves in nature. The GWO has a good performance in some optimization tasks, but its search capacity decreases with the increasing search scope and dimension. This paper proposes an improved GWO (IGWO) algorithm, in which Levy flight strategy and a sine cosine operator with adaptive step are incorporated to significantly improve the performance of the algorithm. The Levy flight strategy is used to strengthen the efficiency of global search. The adaptive sine cosine operator is introduced to improve the local search ability. Experimental results based on twenty unconstrained benchmark problems show the superiority of the proposed IGWO. Furthermore, the IGWO is utilized in PID controller design. The comparison results show that the IGWO algorithm is better than, or at least comparable to, other well-established swarm intelligence algorithms.

关键词： optimization Power system stability Sociology Statistics Prediction algorithms Particle swarm optimization Genetic algorithms

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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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Sliding Mode Estimation-based control for Stochastic Time Delays in Networked Micorgrid 36

Sliding Mode Estimation-based Control for Stochastic Time De...

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第36届中国控制会议

作者： Xuping Zhou Huaicheng Yan Chen Peng Fuwen Yang Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology School of Mechatronic Engineering and Automation Shanghai University School of Engineering Griffith University

ISBN: (纸本)9781538629185

This paper proposes a sliding mode estimation-based control to solve the stochastic time delay problem in networked microgrid,because stochastic delay has a great impact on the stability and performance of large power grids（LPG）.To analyze the delay effects,the microgrid system model is derived according to the characteristics of the inverter in grid-connected *** on the microgrid system model,the stochastic delay estimation with learning parameter and delayed states are *** control signal designed by sliding mode control（SMC） and the learning parameter of delay estimation are adaptively changed in the sliding mode estimation-based control *** reaching law（ERL） is proposed to solve the chattering issues of *** 3.3 KW microgrid parameters are added into simulation to verify the effectiveness and performance of the proposed control strategy.

关键词： Networked Microgrid Sliding Mode control（SMC） Stochastic Delay Estimation

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Variable population memetic search: A case study on the critical node problem

arXiv

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arXiv 2019年

作者： Zhou, Yangming Hao, Jin-Kao Fu, Zhang-Hua Wang, Zhe Lai, Xiangjing School of Information Science and Engineering East China University of Science and Technology 130 Meilong Road Shanghai200237 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Department of Computer Science LERIA Université d'Angers 2 Boulevard Lavoisier Angers49045 France Institut Universitaire de France 1 rue Descartes Paris75231 France Robotics Laboratory for Logistics Service Institute of Robotics and Intelligent Manufacturing Chinese University of Hong Kong Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210023 China

Population-based memetic algorithms have been successfully applied to solve many difficult combinatorial problems. Often, a population of fixed size was used in such algorithms to record some best solutions sampled during the search. However, given the particular features of the problem instance under consideration, a population of variable size would be more suitable to ensure the best search performance possible. In this work, we propose variable population memetic search (VPMS), where a strategic population sizing mechanism is used to dynamically adjust the population size during the memetic search process. Our VPMS approach starts its search from a small population of only two solutions to focus on exploitation, and then adapts the population size according to the search status to continuously influence the balancing between exploitation and exploration. We illustrate an application of the VPMS approach to solve the challenging critical node problem (CNP). We show that the VPMS algorithm integrating a variable population, an effective local optimization procedure (called diversified late acceptance search) and a backbone-based crossover operator performs very well compared to state-of-the-art CNP algorithms. The algorithm is able to discover new upper bounds for 13 instances out of the 42 popular benchmark instances, while matching 23 previous best-known upper bounds. Copyright © 2019, The Authors. All rights reserved.

关键词： Population statistics

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Thermal Decomposition Behavior of Terephthalate in Inert Gas

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China Petroleum Processing & Petrochemical Technology 2017年第3期19卷 1-8页

作者： Yu Jing Wang Jiming Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237 DuPont China Holding Co. LtdShanghai 201203 School of Chemical Engineering East China University of Science and TechnologyShanghai 200237

Several metal terephthalates were synthesized by hydrothermal solvent method. Firstly, the coordination type of metal ions and carboxylates in terephthalate was studied by FTIR spectroscopy. The results showed that the binding type of zinc terephthalate and aluminum terephthalate are mainly bridged coordination, while the chelating coordination mode dominated in the magnesium terephthalate and cerium terephthalate. Secondly, the thermal decomposition mechanism of zinc terephthalate in nitrogen atmosphere was studied by TG and Py-GC/MS techniques. Finally, the activation energy of the thermal decomposition process was obtained by the Friedman method and the Flynn-Wall-Ozawa(FWO) method, and the most probabilistic function was obtained by multiple linear fitting. The results showed that the decomposition process of zinc terephthalate was an one-step reaction and the activation energy was equal to 187.38 kJ/mol.

关键词： terephthalate TG/DTG thermal decomposition mechanism kinetics

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