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A Hybrid Differential Evolution Algorithm Integrated with Particle Swarm Optimization

Journal of Donghua University(English Edition) 2014年第2期31卷 197-200页

作者：范勤勤颜学峰 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

To implement self-adaptive control parameters, a hybrid differential evolution algorithm integrated with particle swarm optimization （PSODE） is proposed. In the PSODE, control parameters are encoded to be a symbiotic individual of original individual, and each original individual has its own symbiotic individual. Differential evolution （ DE） operators are used to evolve the original population. And, particle swarm optimization （PSO） is applied to co-evolving the symbiotic population. Thus, with the evolution of the original population in PSODE, the symbiotic population is dynamically and self-adaptively adjusted and the realtime optimum control parameters are obtained. The proposed algorithm is compared with some DE variants on nine functious. The results show that the average performance of PSODE is the best.

关键词： differential evolution algorithm particle swann optimization self-adaptive co-evolution

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Fault detection based on polygon area statistics of transformation matrix identified from combined moving window data

Fault detection based on polygon area statistics of transfor...

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第26届中国过程控制会议（CPCC2015）

作者： Bei Wang Xuefeng Yan Yongfei Jin Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Department of Mathematics East China University of Science and Technology

As a classic multivariate statistical method, principal component analysis(PCA) has been widely used in monitoring industrial processes, but it is still necessary to make improvements in having a timely and effective access to variation information. It is known that the transformation matrix generated from real-time PCA model indicates inner relations between original variables and new produced components, so this matrix would be different when some variables deviate from the original values area due to the change of the operating condition. Based on this theory, this paper proposes a novel real-time monitoring approach which utilizes polygon area method to measure the variation degree of the transformation matrices and then constructs a statistic for monitoring purpose. The on-line data are collected through a combined moving window(CMW), which contain normal and monitored data at the same time in order to distinguish the faulty data. To evaluate the performance of the proposed method, a simple numerical simulation and the classic Tennessee Eastman process are employed for illustration, with some PCA-based methods used for comparison.

关键词： principal component analysis combined moving window real-time process monitoring fault detection

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External Analysis and Moving Window Lo OP based process monitoring for a class of multi-mode time-varying process

External Analysis and Moving Window Lo OP based process moni...

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第26届中国过程控制会议（CPCC2015）

作者： Yong Gao Xin Wang Zhenlei Wang Liang Zhao Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Center of Electrical & Electronic Technology Shanghai Jiao Tong University

Moving window local outlier probability(MWLo OP)is an outlier detecting method which was proposed for monitoring time-varying industrial processes;however,for the practical industrial processes,besides the time-varying characters caused by deactivation of catalyst,measuring instrument drifting and so on,the operation mode is often switched as the adjusting of the feedstock,changes in market demands and so *** the WMLo OP algorithm can deal with the time-varying process data,the multi-mode process data will lead to a mass of fault *** solve this problem,an external analysis moving window local outlier probability(EA-MWLo OP)algorithm is proposed in this *** external analysis is employed to eliminate the influence of operation mode change on the process data,then the MWLo OP method can deal with complex distribution time-varying data,and give an outlier ***,the corresponding statistic and control limit are constructed to detect the process *** addition,while the monitoring model updated,the control limit is not necessary to *** performance of this method is evaluated through a case study of a non-isothermal continuous stirred tank reactor(CSTR).

关键词： multi-mode time-varying extern analysis non-Gaussian MWLo OP

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Jamming Attack in Centralized State Estimation

Jamming Attack in Centralized State Estimation

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第三十四届中国控制会议

作者： Chao Yang Xiaoqiang Ren Wen Yang Hongbo Shi Ling Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes Dept.of Automation East China University of Science and Technology Dept.of Electronic and Computer Engineering Hong Kong University of Science and Technology

ISBN: (纸本)9781467374439

To understand the behavior of potential network invaders, this paper considers a system attack problem from the perspective of an invader. The invader intends to attack a system, where a group of sensors measure a process state and send the measurements to a remote estimator for state estimation, by launching Denial-of-Service(Do S) attacks to block the communication channels. As the invader has a power budget and cannot block all the channels, he needs to decide which sensors to attack so that the estimation performance can be mostly affected, which is studied in this paper. In the scenario where the sensing abilities of the sensors have a full order, an explicit solution is provided. When the order does not exist, the problem is transformed into a convex optimization problem and is solved using efficient numerical algorithms.

关键词： Networked control systems,security in cyberphysical systems,jamming attack,convex optimization

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Stable Distributed Model Predictive control Strategy Based on Agent Coordination 33

Stable Distributed Model Predictive Control Strategy Based o...

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第三十三届中国控制会议

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

ISBN: (纸本)9781479947249

Many systems composed by several interacting subsystems are usually controlled by a distributed control framework. Distributed Model Predictive control(DMPC) strategy, in which each subsystem is controlled by a local MPC controller, has advantages of accommodating constraints, less computational cost and high flexibility. In order to improve the global performance and guarantee the system stability, a stabilized DMPC strategy is proposed in this paper, in which subsystems interact through inputs. At first, local initial feasible solutions are achieved based on a Minkowski functional to guarantee the local closed-loop system stabilization. And then the global optimal solutions are obtained through coordination strategy for the sake of reducing iteration time and accelerating the convergence speed efficiently. Finally, the accuracy and efficiency of the proposed scheme is put to test through simulation.

关键词： Distributed model predictive control,agent coordination,Stability

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Partition mutation PSO for welding robot path optimization

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2015年 363卷 77-86页

作者： Wang, Xue-Wu Shi, Ying-Pan Gu, Xing-Sheng Ding, Dong-Yan Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China Institute of Microelectronic Materials and Technology School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai200240 China

Many solder joints usually have to be traversed for spot welding robots, and reasonable welding sequence will improve welding efficiency. Intelligent optimization algorithms have been used to study path optimization problems in these years because of their effective optimization abilities. Due to its simplicity, high search accuracy and fast convergence rate, the particle swarm optimization (PSO) algorithm was used to study welding robot path planning. A novel hybrid discrete PSO algorithm was proposed to improve the basic PSO after the partition operation, mutation strategy were combined. Then, the optimization performance of the algorithm was used to solve 3-dimensional welding path planning problem. © Springer International Publishing Switzerland 2015.

关键词： Spot welding

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Event-triggered H∞ Filtering for Networked control Systems with Time-varying Delay 33

Event-triggered H∞ Filtering for Networked Control Systems ...

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第三十三届中国控制会议

作者： YAN Sheng YAN Huaicheng SHI Hongbo ZHAO Haitao Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Information Science and Engineering East China University of Science and Technology

ISBN: (纸本)9781479947249

This paper deals with the H∞filter design problem for event-triggered networked control systems(NCSs), where the next task release time and finishing time are predicted based on the sampled states. The closed-loop filtering error system is modeled as a linear system with an interval time-varying delay and event-triggered communication strategy. Based on this model, some novel criteria for the asymptotic stability analysis and H∞filter design of the event-triggered NCSs with timevarying delay are established to guarantee a prescribed H∞disturbance rejection attenuation level. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

关键词： H∞ filtering,networked control systems,time-varying,event-triggered

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Path Planning for Mobile Anchor Node in Localization Based on Ad-Hoc Localization Algorithm

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Journal of Donghua University(English Edition) 2014年第2期31卷 212-216页

作者：蒲石祁荣宾靳文浩钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology Shanghai Consulting & Academic Activeties Center for Academicians of Chinese Academy of Engineering

For mobile anchor node static path planning cannot accord the actual distribution of node for dynamic adjustment. We take advantage of the high localization accuracy and low computational complexity of ad-hoc localization system( AHLos)algorithm. This article introduces mobile anchor nodes instead of the traditional fixed anchor nodes to improve the algorithm. The result shows that, through introduce the mobile anchor node, the information of initial anchor nodes can be configured more ***,with the use of the approximate location and the transition path,the distance and energy consumption of the mobile anchor node is greatly reduced.

关键词： mobile anchor node path planning ad-hoc localization system(AHLos) approximate location transition path

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Improved shuffled frog leaping algorithm for permutation flow shop scheduling

Improved shuffled frog leaping algorithm for permutation flo...

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2013 International Conference on Information and Communication Technology for education, ICTE 2013

作者： Xu, Zhenhao Xu, Xiao Gu, Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

This paper studies the scheduling problem in a permutation flow shop with the objective of makespan, which is known as one of major problems in the field of scheduling. In order to solving the corresponding model, an improved shuffled frog leaping algorithm (ISFLA) is put forward for this kind of scheduling problem. A new leaping rule based on the characteristic of the problem is devised to improve the performance of the ISFLA. And it can not only produce feasible solutions but also maintain the structure characteristic of the SFLA. Computational experiments on benchmark sets show that the proposed ISFLA is greatly effective to generate good solutions relative to the other two algorithms. © 2014 WIT Press.

关键词： Scheduling

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Dynamic multi-objective optimization of chemical processes using modified Bare-bones MOPSO algorithm 3

Dynamic multi-objective optimization of chemical processes u...

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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： Wang, Shan-Shan Du, Wen-Li Chen, Xu Qian, Feng East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai200237 China

Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering. In this paper, a modified Bare-bones MOPSO algorithm is proposed that takes advantage of few parameters of bare-bones algorithm. To avoid premature convergence, Gaussian mutation is introduced;and an adaptive sampling distribution strategy is also used to improve the exploratory capability. Moreover, a circular crowded sorting approach is adopted to improve the uniformity of the population distribution. Finally, by combining the algorithm with control vector parameterization, an approach is proposed to solve the dynamic optimization problems of chemical processes. It is proved that the new algorithm performs better compared with other classic multi-objective optimization algorithms through the results of solving three dynamic optimization problems.

关键词： Bone

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