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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Kadlic, Branislav Sekaj, Ivan Pernecký, Daniel Institute of Control and Industrial Informatics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9783902823625

An evolutionary computation - based design/optimisation approach using the Cartesian Genetic Programming is proposed for non-linear continuous-time process control. It is a simplification of a more general Genetic Programming - based design, which is powerful, but more computationally demanding. The approach is able to produce effective and non-intuitive controllers in the form of a network of interconnected elementary building blocks, which minimize the defined performance index. Each building block performs mathematic operations between its inputs, next it contains gain and an elementary dynamic part as integrator, derivative or unity gain. The proposed design method is demonstrated on water turbine control design, and the results are compared with the genetic algorithm-based PID controller design. © IFAC.

关键词： controllers

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Model reference adaptive control of glucose in type 1 diabetics: A simulation study 19

Model reference adaptive control of glucose in type 1 diabet...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Tárník, Marián Miklovičová, Eva Murgaš, Ján Ottinger, Ivan Ludwig, Tomáš Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava Ilkovičova 3 Bratislava812 19 Slovakia

ISBN: (纸本)9783902823625

Paper presents the model reference adaptive control applied for the glucose concentration control in Type 1 diabetes mellitus (T1DM) subject. The adaptive controller structure allows to present the commanded insulin infusion by means of the basal infusion rate and the bolus insulin doses. T1DM simulation model is adjusted so that the simulated output corresponds to the particular data logged in a diabetic diary. These facts have allowed to compare the obtained results with the data logged in the diary. © IFAC.

关键词： Model reference adaptive control

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Extracting Patterns of Single-Trial EEG Using an Adaptive Learning Algorithm

Extracting Patterns of Single-Trial EEG Using an Adaptive Le...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Chin-Teng Lin Yu-Kai Wang Chieh-Ning Fang Yi-Hsin Yu Jung-Tai King the Faculty of Engineering and Information Technology University of Technology Sydney (UTS) Australia the Department of Computer Science and Brain Research Center National Chiao-Tung University Taiwan Institute of Electrical Control Engineering and Brain Research Center National Chiao-Tung University Taiwan the Brain Research Center National Chiao-Tung University Taiwan

ISBN: (纸本)9781424492695

The improvement of brain imaging technique brings about an opportunity for developing and investigating brain-computer interface (BCI) which is a way to interact with computer and environment. The measured brain activities usually constitute the signals of interest and noises. Applying the portable device and removing noise are the benefits to real-world BCI. In this study, one portable electroencephalogram (EEG) system non-invasively acquired brain dynamics through wireless transmission while six subjects participated in the rapid serial visual presentation (RSVP) paradigm. The event-related potential (ERP) was traditionally estimated by ensemble averaging (EA) to increase the signal-to-noise ratio. One adaptive filter of data-reusing radial basis function network (DR-RBFN) was also utilized as the estimator. The results showed that this portable EEG system stably acquired brain activities. Furthermore, the task-related potentials could be clearly explored from the limited samples of EEG data through DR-RBFN. According to the artifact-free data from the portable device, this study demonstrated the potential to move the BCI from laboratory research to real-life application in the near future.

关键词： BCI RSVP EA

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Iterative Dynamic Diversity Evolutionary Algorithm for Constrained Optimization

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自动化学报 2014年第11期40卷 2469-2479页

作者： GAO Wei-Shang School of Control Science and Engineering Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian 116024 China Institute of Advanced Control Technology Dalian University of Technology Dalian 116024 China

Evolutionary algorithms (EAs) were shown to be effective for complex constrained optimization problems. However, inflexible exploration in general EAs would lead to losing the global optimum nearby the ill-convergence regions. In this paper, we propose an iterative dynamic diversity evolutionary algorithm (IDDEA) with contractive subregions guiding exploitation through local extrema to the global optimum in suitable steps. In IDDEA, a novel optimum estimation strategy with multi-agents evolving diversely is suggested to efficiently compute dominance trend and establish a subregion. In addition, a subregion converging iteration is designed to redistrict a smaller subregion in current subregion for next iteration, which is based on a special dominance estimation scheme. Meanwhile, an infimum penalty function is embedded into IDDEA to judge agents and penalize adaptively the unfeasible agents with the lowest fitness of feasible agents. Furthermore, several engineering design optimization problems taken from the specialized literature are successfully solved by the present algorithm with high reliable solutions.

关键词：约束优化问题进化算法多样性迭代全局最优最佳估计工程设计代理商

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Optimization of robotic arm trajectory using genetic algorithm 19

Optimization of robotic arm trajectory using genetic algorit...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Števo, Stanislav Sekaj, Ivan Dekan, Martin Institute of Control and Industrial Informatics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkovičova 3 Bratislava812 19 Slovakia

ISBN: (纸本)9783902823625

The paper presents a genetic algorithm - based design approach of the robotic arm trajectory control with the optimization of various criterions. The described methodology is based on the inverse kinematics problem and it additionally considers the minimization of the operating-time, and/or the minimization of energy consumption as well as the minimization of the sum of all rotation changes during the operation cycle. Each criterion evaluation includes the computationally demanding simulation of the arm movement. The proposed approach was verified and all the proposed criterions have been compared on the trajectory optimization of the industrial robot ABB IRB 6400FHD, which has six degrees of freedom. © IFAC.

关键词： Inverse problems

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Characterizing an entangled-photon source with classical detectors and measurements

Characterizing an entangled-photon source with classical det...

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European Quantum Electronics Conference, EQEC 2015

作者： Rozema, L.A. Wang, C. Mahler, D.H. Hayat, A. Steinberg, A.M. Sipe, J.E. Liscidini, M. Centre for Quantum Information and oQuantum Control and Institute for Optical Sciences Department of Physics University of Toronto 60 St. George St. TorontoONM5S 1A7 Canada Faculty of Physics University of Vienna Boltzmanngasse 5 ViennaA-1090 Austria Canadian Institute for Advanced Research TorontoONM5G 1Z8 Canada Department of Electrical Engineering Technion Haifa32000 Israel Dipartimento di Fisica Universit' a degli Studi di Pavia via Bassi 6 PaviaI-27100 Italy

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Robust model predictive controller design 19

Robust model predictive controller design

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Vozák, Daniel Veselý, Vojtech Institute of Control and Industrial Informatics Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava Ilkovičova 3 Bratislava812 19 Slovakia

ISBN: (纸本)9783902823625

This paper addresses to the problem of designing, modelling and practical realization of robust model predictive control which ensures a parameter dependent quadratic stability and guaranteed cost for linear polytopic systems. The design procedure based on BMI and LMI is reduced to off-line output feedback gain calculation. A numerical example and an application to a real process is given to illustrate the effectiveness of the proposed method. © IFAC.

关键词： Feedback

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From linear to nonlinear model predictive control of a building 19

From linear to nonlinear model predictive control of a build...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Pčolka, Matej Žáčeková, Eva Robinett, Rush Čelikovský, Sergej Šebek, Michael Department of Control Engineering Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Mechanical Engineering-Engineering Mechanics Michigan Technological University United States Institute of Information Theory and Automation Academy of Sciences of the Czech Republic Czech Republic

ISBN: (纸本)9783902823625

In the building climate control area, the linear model predictive control (LMPC)- nowadays considered a mature technique-benefits from the fact that the resulting optimization task is convex (thus easily and quickly solvable). On the other hand, while nonlinear model predictive control (NMPC) using a more detailed nonlinear model of a building takes advantage of its more accurate predictions and the fact that it attacks the optimization task more directly, it requires more involved ways of solving the non-convex optimization problem. In this paper, the gap between LMPC and NMPC is bridged by introducing several variants of linear time-varying model predictive controller (LTVMPC). Making use of linear time-varying model of the controlled building, LTVMPC obtains predictions which are closer to reality than those of linear time invariant model while still keeping the optimization task convex and less computationally demanding than in the case of NMPC. The concept of LTVMPC is verified on a set of numerical experiments performed using a high fidelity model created in a building simulation environment and compared to the previously mentioned alternatives (LMPC and NMPC) looking at both the control performance and the computational requirements. © IFAC.

关键词： Model predictive control

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Identification of T1DM minimal model using non-consistent data from IVGTT

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Journal of electrical Systems and information Technology 2014年第2期1卷 144-149页

作者： Tomas Ludwig Ivan Ottinger Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava Slovak Republic

Type 1 diabetes mellitus identification using inconsistent data from IVGTT (Intravenous Glucose Tolerance Test) of healthy subject is presented in this paper. Simple PID (Proportional – Integral – Derivative) contro... 详细信息

关键词： Type 1 diabetes mellitus Identification IVGTT Linearization PID

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Continuous Travel Time Prediction for Transit Signal Priority Based on a Deep Network

Continuous Travel Time Prediction for Transit Signal Priorit...

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International Conference on Intelligent Transportation

作者： Xiong Gang Wenwen Kang Feiyue Wang Fenghua Zhu Yisheng Lv Xisong Dong Jukka Riekki Susanna Pirttikangas State Key Lab. of Manage. & Control for Complex Syst. Institute of Automation Chinese Academy of Sciences Beijing Beijing CN The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Cloud Computing Center Chinese Academy of Sciences Dongguan CHINA Faculty of Information Technology and Electrical Engineering University of Oulu Finland

It has been recognized by many researchers that accurate bus travel time prediction is critical for successful deployment of traffic signal priority (TSP) systems. Although there exist a lot of studies on travel time prediction for Advanced Traveler information Systems (ATIS), this problem for TSP purpose is a little different and the amount of literature is limited. This paper proposes a deep learning based approach for continuous travel time prediction problem. Parameters of the deep network are fine-tuned following a layer-by-layer pre-training procedure on a dataset generated by traffic simulations. Variables that may affect continuous travel time are selected carefully. Experiments are conducted to validate the performance of the proposed model. The results indicate that the proposed model produces prediction with mean absolute error less than 4 seconds, which is accurate enough for TSP operations. This paper also reveals that, except for obvious factors like speed, travel distance and traffic density, the signal time when the prediction is made is also an important factor affecting travel time.

关键词： Vehicles Predictive models Object oriented modeling Training Artificial neural networks Data models

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