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International Conference on Natural Computation (ICNC)

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

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.

关键词： Heuristic algorithms optimization Immune system Aerodynamics Algorithm design and analysis Evolutionary computation Vectors

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Modeling growth of microalgae Dunaliella salina under different nutritional conditions

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American Journal of Biochemistry and Biotechnology 2010年第4期6卷 279-283页

作者： Jesus, Sergio Santos Filho, Rubens Maciel Department of Chemical Process Laboratory of Optimization Design and Advanced Control School of Chemical Engineering University of Campinas Unicamp Cidade Universitária Zeferino Vaz CP 6066 Campinas SP Brazil

Problem statement: The aim of this study was to find the empirical model that describes the growth kinetics of Dunaliella salina, with low production cost and to estimate parameters of this model. Approach: In this study the strain of D. salina UTEX 200 was cultivated in seawater (0.5 M NaCl) at room temperature with agitation of 150 rpm and luminous intensity of 60 mmols.m-2.s-1. The synthetic medium AS100 (0.2 M NaCl) was used in this study for comparison purposes and in order to determine the optimal growth of the microalgae. Kinetics of growth and β-carotene production was determined in a period of 15 days. Results: After the analysis of the behavior graphic, an unstructured model was used for describing the cell growth (logistic model). It was observed that the model was well adjusted to experimental data for the two conditions of analysis. It was observed that alga produces carotenoids under conditions of stress, in which the cell division are retarded. In the case of cells grown in seawater (higher salt concentration), the cell growth was lower but the concentration of β-carotene was higher. Conclusion: In general, these results suggest that D. salina presents higher potential for β-carotene accumulation and that high salinity decreases cellular concentration (measured by the parameter Xm of the kinetic model proposed);however there is an increase in β-carotene production. © 2010 Science Publications.

关键词： Microalgae

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An immune inspired approach to 802.11 Wireless LANs coverage optimization

An immune inspired approach to 802.11 Wireless LANs coverage...

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International Conference on Information Networking and Automation (ICINA)

作者： Xuan Zhou Rongbin Qi Qian Li Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China School of Electronics and Information University of Tongji Shanghai China

ISBN: (纸本)9781424481040

Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the BS's (Base Station) sites. Compared the results of opt-aiNet and genetic algorithms(GA) which have been used in radio coverage optimization before, we found that opt-aiNet could find the optimal solution all times while GA falling into local optimum solution sometimes, and opt-aiNet converged more quickly than GA in most cases. Experimental results show that opt-aiNet is an effective way to optimize the 802.11 Wireless LANs planning problems.

关键词： Education Gallium Indexes Computational modeling

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On Line Estimation of Color Values (B*) In Pet Process Using Gaussian Process Regression

On Line Estimation of Color Values (B*) In Pet Process Using...

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The 8th World Congress on Intelligent control and Automation(第八届智能控制与自动化世界大会 WCICA 2010)

作者： Na Luo Feng Qian School of Information Science and Engineering Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 P.R.China

With improvement of PET quality, the color of PET is required to be controlled. But the mechanism model of PET color is not so clear. In this paper, a modeling method of color values (B*) is introduced. It is based on sparse pseudo-input gaussian process. Online correction is added to the modeling based on sliding time window. Comparing to support vector regression, the model using gaussian process gives both prediction and predictive variance. The results show that B* value model using gaussian process is more flexible and can be used in real process.

关键词： Positron emission tomography Color Joints

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Reduced-order multiple models robust direct adaptive control of non-minimum phase system

Reduced-order multiple models robust direct adaptive control...

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World Congress on Intelligent control and Automation (WCICA)

作者： J.-Z. Liu Z.-L. Wang Xin Wang D.-H. Wang Feng Qian 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 Engineering Shanghai Jiaotong University Shanghai China

The performance of robust adaptive control system based on traditional revised algorithm is awful in the presence of unmodeled dynamics and the performance will go bad, even be unstable, when the working condition (including the parameter, reference input, and so on) change. This paper designs the multiple models robust adaptive controller to control the discrete single-variable non-minimum phase system. First, the higher part of the system is deem to be the unmodelled dynamic and the normalization is introduced to convert the system unmodeled dynamics to bounded disturbance as well as the dead zone is introduced in parameter update algorithm. And then, the multiple models robust adaptive controllers are designed based on the lower part of the system and the best controller is chosen based on the switch index to control the system. The last simulation illustrates that the proposed method is preferable even the working condition changes.

关键词： Adaptation model Adaptive control Robustness Heuristic algorithms Switches

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Loss-model-based efficiency optimization control for asynchronous motor using fuzzy-logic

Loss-model-based efficiency optimization control for asynchr...

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Chinese control Conference (CCC)

作者： Liping Fan Yi Liu Ying Shu Key Laboratory for Cooperative Control and Optimization Techniques on Industrial Environment and Resources of the Education Department of Liaoning Province Shenyang University of Chemical Technology 110142 China Steel Rolling Division Northern Heavy Industries Group Co. Ltd Shenyang 110142 China

It is estimated that more than 50% of the world electric energy generated is consumed by electric machines. In face of the dual-pressure of energy shortage and environmental degradation, it is a burning question to improve the running efficiency of electric motors. In this paper, the relationship between the minimal loss and the flux of asynchronous motor is studied, and based on this, a loss model based fuzzy logic control strategy is adopted to realize efficiency optimization control for asynchronous motor. Simulation results show that the proposed control method can minish motor loss effectively, and it has feasibility and effectiveness on energy saving for motors.

关键词： Iron Niobium Induction motors optimization Fuzzy logic Estimation Electric motors

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Quantum clustering-based weighted linear programming support vector regression for multivariable nonlinear problem

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Soft Computing 2009年第9期14卷 921-929页

作者： Yu, Yanfang Qian, Feng Liu, Huimin Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

Linear programming support vector regression shows improved reliability and generates sparse solution, compared with standard support vector regression. We present the v-linear programming support vector regression approach based on quantum clustering and weighted strategy to solve the multivariable nonlinear regression problem. First, the method applied quantum clustering to variable selection, introduced inertia weight, and took prediction precision of v-linear programming support vector regression as evaluation criteria, which effectively removed redundancy feature attributes and also reduced prediction error and support vectors. Second, it proposed a new weighted strategy due to each data point having different influence on regression model and determined the weighted parameter p in terms of distribution of training error, which greatly improved the generalization approximate ability. Experimental results demonstrated that the proposed algorithm enabled the mean squared error of test sets of Boston housing, Bodyfat, Santa dataset to, respectively, decrease by 23.18, 78.52, and 41.39%, and also made support vectors degrade rapidly, relative to the original v-linear programming support vector regression method. In contrast with other methods exhibited in the relevant literatures, the present algorithm achieved better generalization performance.

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Evolutionary algorithm using kernel density estimation model in continuous domain

Evolutionary algorithm using kernel density estimation model...

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Asian control Conference

作者： Na Luo Feng Qian Key Laboratory of Advanced Control and Optimization of Chemical Process Ministry of Education State Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai China Key Laboratory of Advanced Control and Optimization of Chemical Process Ministry of Education State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai China

ISBN: (纸本)9781424454402

Estimation of distribution algorithm (EDA) is a kind of evolutionary algorithm which updates and samples from probabilistic model in evolutionary course. The key of EDA is the construction of probability model suitable for real distribution. Gaussian distribution is widely used in EDAs but the assumption of normality is not realistic for many real-life problems. In this paper, a new EDA using kernel density estimation (KEDA) is introduced. Adaptive change strategy of kernel width is presented and selection scheme, sampling method are also given cooperated with KEDA. The results of 5 benchmark functions show that results of KEDA outperform PBIL C , UMDA C , EDA G , H-EDA.

关键词： Evolutionary computation Kernel Electronic design automation and methodology Laboratories Histograms Density functional theory Gaussian distribution Automatic control chemical processes control engineering education

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controlling the transport of single photons by tuning the frequency of either one or two cavities in an array of coupled cavities

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Physical Review A 2010年第4期81卷 042304-042304页

作者： Jie-Qiao Liao (廖洁桥) Z. R. Gong (龚志瑞) Lan Zhou (周兰) Yu-xi Liu (刘玉玺) C. P. Sun (孙昌璞) Franco Nori (野理) Advanced Science Institute The Institute of Physical and Chemical Research (RIKEN) Wako-shi 351-0198 Japan Institute of Theoretical Physics Chinese Academy of Sciences Beijing 100190 People's Republic of China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Hunan Normal University Changsha 410081 People's Republic of China and Department of Physics Hunan Normal University Changsha 410081 People's Republic of China Institute of Microelectronics Tsinghua University Beijing 100084 People's Republic of China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 People's Republic of China Physics Department The University of Michigan Ann Arbor Michigan 48109-1040 USA

We theoretically study how to control transport, bound states, and resonant states of a single photon in a one-dimensional coupled-cavity array. We find that the transport of a single photon in the cavity array can be controlled by tuning the frequency of either one or two cavities. If one of the cavities in the array has a tunable frequency, and its frequency is tuned to be larger (or smaller) than those of other cavities, then there is a photon bound state above (or below) the energy band of the coupled-cavity array. However, if two cavities in the array have tunable frequencies, then there exist both bound states and resonant states. If the frequencies of the two cavities are chosen to be much larger than those of other cavities, and the hopping couplings between any two nearest-neighbor cavities are weak, then a single photon with a resonant wave vector can be trapped in the region between the two frequency-tunable cavities. In this case, a quantum supercavity can be formed by these two frequency-tunable cavities. We also study how to apply this photon transport control to an array of coupled superconducting transmission line resonators.

关键词： Photons

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Performance assessment of run-to-run control in semiconductor manufacturing based on IMC framework

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International Journal of Production Research 2009年第15期47卷 4173-4199页

作者： Chen, Liang Ma, Mingda Jang, Shi-Shang Wang, David Shan-Hill Wang, Shuqing State Key Laboratory of Industrial Control Technology Institute of Advanced Process Control Hangzhou China Center for Control and Guidance Technology Harbin Institute of Technology Harbin China Department of Chemical Engineering National Tsing-Hua University Hsin-Chu Taiwan

The objective of this paper is to propose a universal methodology for performance assessment of run-to-run control in semiconductor manufacturing. The slope of the linear semiconductor process model is assumed to be known or subjected to mild plant/model mismatch. Based on an internal model control framework, analytical expressions of minimum variance performance (MVP) and best achievable performance (BAP) for a series of run-to-run control schemes are derived. In the methodology, closed-loop identification is utilised as the first step to estimate the noise dynamics via routine operating data, and numerical optimisation is employed as a second step to calculate the best achievable performance bounds of the run-to-run control loops. The validity of the methodology is justified by examples of performance assessment for EWMA control, double EWMA control and RLS-LT control, even under circumstances where the processes encounter model mismatch, metrology delay and more sophisticated noises. Several essential characteristics of run-to-run control are discovered by performance assessment, and valuable advice is offered to process engineers for improving the run-to-run control performance. Furthermore, a useful application example for online performance monitoring and optimal tuning of run-to-run controller demonstrates the advantage of the methodology.

关键词： optimization

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