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American control Conference

作者： Chunyu Yang Qingling Zhang Jyh-Horng Chou Yingwei Zhang Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110004 P.R. China Institute of Systems Science Northeastern University Shenyang 110004 P.R. China Institute of System Information and Control Engineering National Kaohsiung First University of Science and Technology I University Road Yuanchau Kaohsiung 824 Taiwan

ISBN: (纸本)9781424474264

This paper investigates the absolute stability problem for Lur'e singularly perturbed systems with multiple nonlinearities. The objective is to determine if the system is absolutely stable for any epsilon E (0, (epsilon)_(0)], where epsilon denotes the perturbation parameter and (epsilon)_(0) is a pre-defined positive scalar. Firstly, an epsilon-dependent Lyapunov function of Lur'e-postnikov form is constructed. Then, a stability criterion expressed in terms of epsilon-independent linear matrix inequalities (LMIs) is derived. Finally, an example is given to show the feasibility and effectiveness of the obtained method.

关键词： Robust stability Stability criteria control systems Lyapunov method Power system stability Power system modeling Educational institutions Nonlinear control systems control nonlinearities USA Councils

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Improved Multidisciplinary Multiobjective Collaborative Optimization Technique Based on NSGA-II Algorithm 1

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IFAC Proceedings Volumes 2010年第25期43卷 139-144页

作者： H. Li Y. Jing S. Zhang V. Ojleska T. Kolemisevska G.M. Dimirovski Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110004 P.R. China Northeastern University School of Information Science & Engineering Shenyang 110004 P.R. China SS Cyril and Methodius University School FEIT Institute of ASE Karpos II BB MK-1000 Skopje R. Macedonia Dogus University Computer Eng. and Control Eng. Departments TR-34722 Istanbul Turkey

The multiobjective collaborative optimization (MCO) has been widely adopted in concurrent engineering design as a good multiobjective optimization approach provided the problem of optimization results converging often to a local extremum has been taken care of. It has been demonstrated to yield useful solutions to a wide range of optimization problems under concurrent condition both technical and non-technical ones. A solution strategy for MCO that overcomes this drawback is proposed here on the grounds of genetic NSGA-II algorithm. It is an adaptive heuristic search technique that controls the distances between the individual and system's feasible region during genetic evolution. In the evolving NSGA-II based non-dominated sorting, the individual threshold of infeasibility degree is reduced gradually via genetic evolution and the individual's feasibility capacity is determined by its infeasibility degree and the threshold. It has been applied to a benchmark example of speed reducer design, and the obtained results demonstrate the proposed technique is comparably more efficient and may offer substantial advantages over the gradient-based optimization methods. Copyright © 2010 IFAC

关键词： Collaborative optimization dynamic threshold genetic algorithms multidisciplinary optimization multiobjective optimization

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Force-induced bone growth and adaptation: A system theoretical approach to understanding bone mechanotransduction

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IOP Conference Series: Materials Science and engineering 2010年第1期10卷

作者： Solvey Maldonado Rolf Findeisen Laboratory for Systems Theory and Automatic Control Institute for Automation Engineering (IFAT) Otto-von-Guericke-Universität Magdeburg 39106 Magdeburg Germany

The modeling, analysis, and design of treatment therapies for bone disorders based on the paradigm of force-induced bone growth and adaptation is a challenging task. Mathematical models provide, in comparison to clinical, medical and biological approaches an structured alternative framework to understand the concurrent effects of the multiple factors involved in bone remodeling. By now, there are few mathematical models describing the appearing complex interactions. However, the resulting models are complex and difficult to analyze, due to the strong nonlinearities appearing in the equations, the wide range of variability of the states, and the uncertainties in parameters. In this work, we focus on analyzing the effects of changes in model structure and parameters/inputs variations on the overall steady state behavior using systems theoretical methods. Based on an briefly reviewed existing model that describes force-induced bone adaptation, the main objective of this work is to analyze the stationary behavior and to identify plausible treatment targets for remodeling related bone disorders. Identifying plausible targets can help in the development of optimal treatments combining both physical activity and drug-medication. Such treatments help to improve/maintain/restore bone strength, which deteriorates under bone disorder conditions, such as estrogen deficiency.

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Fault management for a Three Mass Torsion Oscillator 10

Fault management for a Three Mass Torsion Oscillator

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2009 10th European control Conference, ECC 2009

作者： Bahr, Joachim Munchhof, Marco Isermann, Rolf Institute of Automatic Control Laboratory for Control Systems and Process Automation Technische Universität Darmstadt Landgraf-Georg-Str. 4 Darmstadt64283 Germany

ISBN: (纸本)9783952417393

A model-based fault management system for a Three Mass Torsion Oscillator is described. Fault management includes fault detection, fault diagnosis and fault compensation. A process model of system dynamics is derived. Friction effects are modelled by a neuro-fuzzy Local Linear Model Tree (LOLIMOT) approach. Parameter estimation is obtained with two simple experiments. A friction estimation stage is used to support fault diagnosis and potential control applications. Parity equations are used to detect and diagnose speed sensor failures. In case of sensor failures, the fault management system initiates reconfiguration operations. The failure of one sensor is compensated by substituting the sensor signal with the output of a process model fed by other, intact sensors. The methods presented are evaluated using experimental measurements of a test rig. © 2009 EUCA.

关键词： Failure analysis

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Identification of Nonlinear Static processes with Local Polynomial Regression and Subset Selection

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IFAC Proceedings Volumes 2009年第10期42卷 138-143页

作者： Heiko Sequenz Alexander Schreiber Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Germany (Tel: +49-6151-16 3914

The presented method for nonlinear system identification is based on the LOLIMOT algorithm introduced by Nelles and Isermann [1996]. The LOLIMOT algorithm divides the input space by a tree-construction algorithm and interpolates the local linear models by local membership functions. Instead of assuming local linear models, the presented algorithm utilizes general local nonlinear functions, which make the algorithm more flexible. These are approximated by a multidimensional Taylor series. Since the amount of regressors grows fast with the number of inputs and the expansion order, a subset selection procedure is introduced. It reveals significant regressors and gives information about the local functional behavior. The local subset selection is implemented as a stepwise regression with replacement of regressors. Mallows’ C p -statistic is used for the subset selection algorithm and is also implemented for final model selection. The benefit of the extended algorithm lies in the higher flexibility in the local models, which results in less partitions of the input space by a similar approximation quality.

关键词： Local Regression Subset Selection LOLIMOT Identification Algorithm Multivariate Polynomials Least-Squares Estimation Automotive Emissions

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Neural-Net Model Based Fault Diagnosis for Hydraulic Servo Axes

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IFAC Proceedings Volumes 2009年第8期42卷 1097-1102页

作者： Marco Muenchhof Sebastian Clever Technische Universität Darmstadt Institute of Automatic Control Laboratory for Control Systems and Process Automation 64283 Darmstadt Germany

In this paper, fault detection methods for hydraulic systems based on a parity equation approach with neural net models are presented. Hydraulic systems are used in manifold applications in industry. They are however not yet the subject of intense research in the area of fault detection and diagnosis, which can be mainly attributed to their strong nonlinear behavior, which exacerbates the physical modeling extensively. To avoid the difficulties associated with the physical modeling, a data-driven modeling approach based on the LOLIMOT neural network will be presented in this paper. Different subsystems of the hydraulic servo axis will be modeled using different sensor configurations. Experimental data from a real testbed allow to compare the model fidelity of the different resulting neural nets and can also be used to illustrate the capabilities of the parity-equation based fault detection approach, which in general allows the detection of tiny faults, such as sensor offset faults in the area of a few percent of the maximum sensor readout.

关键词： Fault detection fault diagnosis hydraulic servo systems modeling neural nets

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Fault Tolerant Actuators and Drives – Structures, Fault Detection Principles and Applications

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IFAC Proceedings Volumes 2009年第8期42卷 1294-1305页

作者： Marco Muenchhof Mark Beck Rolf Isermann Technische Universität Darmstadt Institute of Automatic Control Laboratory for Control Systems and Process Automation Darmstadt Germany (Tel: +49-6151-16-3114) Technische Universität Darmstadt Institute of Automatic Control Laboratory for Control Systems and Process Automation Darmstadt Germany (Tel: +49-6151-16-2314) Technische Universität Darmstadt Institute of Automatic Control Laboratory for Control Systems and Process Automation Darmstadt Germany (Tel: +49-6151-16-2114)

As fault detection and fault diagnosis are more and more finding their way into modern industrial mechatronic products, it is now time to take the next step. Based on the research efforts for fault detection and diagnosis, a platform has been prepared for research on fault management, i.e. automatic reactions of the system to continue operation after the detection of faults. These reactions may employ hardware redundancy (i.e. switching from a faulty actuator to another, intact one) or analytical redundancy (i.e. switching from a faulty sensor to a “model sensor” or “soft sensor”). A total fault tolerance concept must encompass all components of a system, i.e. the actuators and drives, the sensors as well as the controller and communication. In many cases, a degradation of functions has to be accepted after a fault has appeared. This contribution will center on actuators and drives showing real-world examples of prototypical realizations and examples from industrial products. Concentrating on the most widespread actuation principles, the paper will focus on electric drives and hydraulic actuators. First, a review is given on fault tolerance principles and general structural considerations e.g. hot-standby and cold-standby, focusing on the scheme of an overall fault-tolerant control system. Then, fault statistics for real actuators and drives will be presented. These fault statistics give hints on the parts of the actuators that are most susceptible to faults. Different designs of fault tolerant actuators and drives, which have been realized, shall be presented and evaluated with respect to their capabilities of sustaining faults. Finally, an outlook for fault-tolerant mechatronic systems will be given.

关键词： Sensor and actuator faults structural analysis aerospace applications automotive applications electro-mechanical applications other applications

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Real time optimisation for thermal processes 10

Real time optimisation for thermal processes

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2009 10th European control Conference, ECC 2009

作者： Garcia, Miriam R. Vilas, Carlos Balsa-Canto, Eva Alonso, Antonio A. Hamilton Institute NUIM Ireland Automatic Control Laboratory Facult Polytechnique de Mons Belgium Process Engineering Group IIM-CSIC Vigo Spain

ISBN: (纸本)9783952417393

This work presents the theoretical design and the experimental validation of a real time optimisation logic for distributed parameter systems. This logic consists of a hierarchy of two layers. The upper layer is responsible of obtaining the optimal control profile by a suitable combination of the control vector parameterisation approach with a hybrid global-local optimiser and the use of reduced models for distributed parameter systems. The lower layer corresponds to a PID controller designed in the framework of Internal Model control to keep tracking capabilities at short time scales. This logic was applied to the real time optimisation of the thermal processing of packaged foods in batch retorts at the pilot plant available at the IIM-CSIC. The objective was to maximise food product quality while satisfying safety constraints. The proposed scheme was able to optimally operate the system under standard plant perturbations and under a pressure drop. © 2009 EUCA.

关键词： Model predictive control

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Spatial Distribution of Land Cover and Vegetation Activity along Topographic Gradient in an Arid River Valley, SW China

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Journal of Mountain Science 2009年第3期6卷 274-285页

作者： LIU Wen XU Xianli LUO Jiancheng SHEN Zhanfeng ZHONG Qiuhai Department of Automatic Control School of Automation Beijing Institute of Technology Beijing 100081 China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China Centre for Hydrology Micrometeorology and Climate Change Department of Civil and Environmental Engineering University College Cork Cork Ireland

Anthropogenic activities have become more and more important in characterizing the landscape, but their impacts are still restricted by natural environments. This paper discusses the interactions of anthropogenic activity, vegetation activity and topography through describing the spatial distribution of land cover and vegetation activity (represented by Normalized Difference Vegetation Index, NDVI) along topographic gradient in a mountainous area of southwestern China. Our results indicate that the existing landscape pattern is controlled by anthropogenic activities as well as topographic factors. Intensive anthropogenic activities mainly occur in areas with relatively low elevation, gentle and concave slopes, as these areas are easy and convenient to attain for human. Because of the destruction by human, some land cover types (mainly grassland and shrub) are only found in relatively harsher environments. This study also finds that topographic wetness index (W) used in other places only reflects runoff generation capacity, but not indicate the real spatial pattern of soil water content in this area. The relationships between NDVI and W, and NDVI and length slope factor (LSF) show that runoff and erosion have complex effects on vegetation activity. Greater values of W and LSF will lead to stronger capacity to produce runoff and transport sediment, and thereby increase soil water content and soil deposition, whereas beyond a certain threshold runoff and erosion are so strong that they would destruct vegetation growth. This study provides information needed to successfully restore native vegetation, improve land management, and promote sustainable development in mountainous areas, especially for developing regions.

关键词： Vertical distribution of land cover Anthropogenic activity Vegetation activity Environmental variability China

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An adaptive weight PSO for rolling schedules multi-objective optimization of tandem cold rolling

An adaptive weight PSO for rolling schedules multi-objective...

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IEEE International Conference on automation and Logistics

作者： Yu Wang Yong Li Jianchang Liu Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang Liaoning China Department of Automatic Control Shenyang Institute of Aeronautical Engineering Shenyang Liaoning China

In this paper, an adaptive weight particle swarm optimization is proposed for multi-objective optimization. And it is applied to rolling schedules multi-objective optimization of tandem cold rolling. According to the demands of actual rolling schedules designing, power distribution, rolling energy consumption and slip rate are selected as objective functions. Then the multi-objective model of rolling schedules is established. The proposed algorithm is applied to rolling schedules optimization of tandem cold rolling. The result shows that the proposed method decreases the values of three objective functions simultaneously compared to actual rolling schedules. Furthermore the proposed algorithm has faster convergence speed than the adaptive weight approach GA.

关键词： Job shop scheduling Particle swarm optimization Optimization methods Power distribution Scheduling algorithm automation Energy consumption Logistics Laboratories Convergence

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