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A Typical Power Allocation for Distributed Filtering

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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Tracking performance limitations of mimo networked control systems with multiple communication constraints

arXiv

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arXiv 2019年

作者： Chen, Chao-Yang Gui, Weihua Wu, Lianghong Liu, Zhaohua Yan, Huaicheng School of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan411201 China School of Information Science and Engineering Central South University Changsha410012 China Center for Polymer Studies Department of Physics Boston University BostonMA02215 United States School of Information Science and Engineering Central South University Changsha410012 China School of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan411201 China Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai200237 China College of Mechatronics and Control Engineering Hubei Normal University Huangshi435002 China

In this paper, the tracking performance limitation of networked control systems (NCSs) is studied. The NCSs is considered as continuous-time linear multi-input multi-output (MIMO) systems with random reference noises. The controlled plants include unstable poles and non-minimum phase (NMP) zeros. The output feedback path is affected by multiple communication constraints. We focus on some basic communication constraints, including additive white noise (AWN), quantization noise, bandwidth, as well as encoder-decoder. The system performance is evaluated with the tracking error energy, and used a two-degree of freedom (2DOF) controller. The explicit representation of the tracking performance is given in this paper. The results indicate the tracking performance limitations rely to internal characteristics of the plant (unstable poles and NMP zeros), reference noises (the reference noise power distribution (RNPD) and its directions) and the characteristics of communication constraints. The characteristics of communication constraints include communication noise power distribution (CNPD), quantization noise power distribution (QNPD), and their distribution directions, transform bandwidth allocation (TBA), transform encoder-decoder allocation (TEA), and their allocation directions, and NMP zeros and MP part of bandwidth. Moreover, the tracking performance limitations are also affected by the angles between the each transform NMP zero direction and RNPD direction, and these angles between each transform unstable poles direction and the direction of communication constraint distribution/allocation. In addition, for MIMO NCSs, bandwidth (there are not identical two channels) always can affects the direction of unstable poles, and the channel allocation of bandwidth and encode-decode may be used for a feasible method for the performance allocation of each channels. Lastly, a instance is given for verifying the effectiveness of the theoretical outcomes. Copyright © 2019, The Aut

关键词： Bandwidth

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Hybrid Consensus-based Algorithm for Distributed Economic Dispatch Problem

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IFAC-PapersOnLine 2017年第1期50卷 177-182页

作者： Liu X.-K. Wang Y.-W. Yan H. Wang X. Hu X. School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education China Key Laboratory of Advanced Control Optimization for Chemical Process of Ministry of Education China School of Information Science and Engineering East China University of Science and Technology 130 Meilong Road Shanghai 200237 China

Economic dispatch is one of the fundamental problems in the power system research. The existing algorithms are either discrete iterative algorithms or continuous-time dynamical algorithms. By virtue of the hybrid techniques, a hybrid consensus-based algorithm is proposed in this paper, which consists of a finite-time continuous-time algorithm and a discrete-time interacted scheme. Moreover, inspired by the cluster synchronization and the benefit of the projection operator, a supervised strategy is carried out to ensure that each generator unit will work within its power generation constraint. For a better understanding of the supervised hybrid distributed algorithm, the detailed pseudo-code is presented. Finally, a numerical example is given to illustrate the effectiveness of the algorithm. © 2017

关键词： consensus protocol distributed optimization economic dispatch hybrid system smart grid

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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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Fuzzy-Model-Based Leader-Follower Consensus of Nonlinear Multi-Agent Systems with Input Saturation

Fuzzy-Model-Based Leader-Follower Consensus of Nonlinear Mul...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Xiaolu Liu Duxin Chen Yan-Wu Wang Huaicheng Yan School of Automation Huazhong University of Science and Technology Wuhan P. R. China School of Mathematics Southeast University Nanjing P. R. China Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai P. R. China

This paper presents a fuzzy-model-based method for solving the consensus problem of a class of nonlinear multi-agent systems (MASs) with input saturation. Since each agent has nonlinear dynamics, the system is not asymptotically null controllable with bounded controls (ANCBC). Therefore, the widely-used low-gain feedback method for designing consensus protocols of MASs with input saturation can no longer work. To this end, the Takagi-Sugeno (T-S) fuzzy model is adopted to formulate the error dynamics of those nonlinear follower agents with input saturation as well as a leader with time-varying states. Accordingly, by using the properties of convex hull, a set of invariance condition in the format of linear matrix inequality (LMI) is designed. Furthermore, by enlarging the shape reference set, the estimation of the attraction domain can be obtained. Simultaneously, by viewing the control gain as an extra free parameter in the LMI optimization procedure, the leader-follower consensus algorithm is proposed, which guarantees that all followers with input saturation can track the leader, and they can asymptotically reach consensus. Finally, numerical experiments validate the effectiveness of the proposed anti-saturation consensus algorithm.

关键词： Automation Nonlinear dynamical systems STEM Actuators Symmetric matrices

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DE based economic control chart design and application for a typical petrochemical process

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Frontiers of Engineering Management 2017年第3期4卷 348-356页

作者： Zhi LI Feng QIAN Wenli DU Weimin ZHONG Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

Petrochemical industry plays an important role in the development of the national economy. Purified terephthalic acid(PTA) is one of the most important intermediate raw materials in the petrochemical and chemical fiber industries. PTA production has two parts:p-xylene(PX) oxidation process and crude terephthalic acid(CTA) hydropurification process. The CTA hydropurification process is used to reduce impurities, such as 4-carboxybenzaldehyde, which is produced by a side reaction in the PX oxidation process and is harmful to the polyester industry. From the safety and economic viewpoints, monitoring this process is necessary. Four main faults of this process are analyzed in this study. The common process monitoring methods always use T^2 and SPE statistic as control limits. However, the traditional methods do not fully consider the economic viewpoint. In this study, a new economic control chart design method based on the differential evolution(DE) algorithm is developed. The DE algorithm transforms the economic control chart design problem to an optimization problem and is an excellent solution to such problem. Case studies of the main faults of the hydropurification process indicate that the proposed method can achieve minimum profit *** method is useful in economic control chart design and can provide guidance for the petrochemical industry.

关键词： petrochemical PTA economic control chart design process monitoring DE algorithm

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Orthogonal nonnegative matrix factorization based local hidden Markov model for multimode process monitoring

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Chinese Journal of chemical Engineering 2016年第7期24卷 856-860页

作者： Fan Wang Honglin Zhu Shuai Tan Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

Traditional data driven fault detection methods assume that the process operates in a single mode so that they cannot perform well in processes with multiple operating modes. To monitor multimode processes effectively,this paper proposes a novel process monitoring scheme based on orthogonal nonnegative matrix factorization(ONMF) and hidden Markov model(HMM). The new clustering technique ONMF is employed to separate data from different process modes. The multiple HMMs for various operating modes lead to higher modeling *** proposed approach does not presume the distribution of data in each mode because the process uncertainty and dynamics can be well interpreted through the hidden Markov estimation. The HMM-based monitoring indication named negative log likelihood probability is utilized for fault detection. In order to assess the proposed monitoring strategy, a numerical example and the Tennessee Eastman process are used. The results demonstrate that this method provides efficient fault detection performance.

关键词： Multimode processFault detectionHidden Markov modelOrthogonal nonnegative matrix factorization

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FRDPC subspace construction integrated with Bayesian inference for efficient monitoring of dynamic chemical processes 36

FRDPC subspace construction integrated with Bayesian inferen...

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第36届中国控制会议

作者： Yang Wang Qingchao Jiang Jingqi Fu School of Mechatronic Engineering and Automation Shanghai University School of Electric Engineering Shanghai Dianji University Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

ISBN: (纸本)9781538629185

Modern chemical processes are usually characterized by large-scale,complex correlation,and strong dynamics,and monitoring of such processes is *** paper proposes a performance-driven fault-relevant dynamic principal component(FRDPC) subspace construction integrated with Bayesian inference method to achieve efficient monitoring for dynamic chemical ***,dynamic principal component analysis is employed to deal with both auto-correlation and cross-correlation among ***,considering fault information has no definite mapping to a certain dynamic principal component(DPC) and the existence of non-beneficial DPCs may cause redundancy in the monitoring,an FRDPC subspace is constructed for each fault through the performance-driven DPC *** new process measurements are examined in each FRDPC subspace as well as the residual *** monitoring results in all subspaces are fused to a comprehensive index through Bayesian inference to provide an intuitive indication of the process *** studies on a numerical example and the Tennessee Eastman benchmark process indicate the efficiency.

关键词： fault detection dynamic principal component analysis Bayesian inference dynamic chemical processes

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