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International Colloquium on Signal Processing & Its Applications, CSPA

作者： N.H Sunar M.F. Rahmat Z. H. Ismail A. M. Faudzi Sy Najib Sy Salim Sharatul Izah Samsudin Department of Mechatronics and Control Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia Department of Control Instrument and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia Department of Industrial Electronics Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia

In this paper, two optimization techniques of Particle Swarm Optimization (PSO) and Firefly Algorithm (FA) is used to obtain the optimal PID control parameters. To represent the model of the system, system identification with ARX model structure is developed. The results are determined by analysis the step response characteristic of the system. It was observed that the performances of PID controller with PSO optimized parameters perform well in position tracking of the pneumatic actuator system.

关键词： Tuning Zinc Optimization Signal processing algorithms PD control Pneumatic actuators

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Exponential stability of boundary controlled port Hamiltonian systems with dynamic feedback

Exponential stability of boundary controlled port Hamiltonia...

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1st IFAC Workshop on Control of Systems Governed by Partial Differential Equations, CPDE 2013

作者： Ramirez, Hector Zwart, Hans Le Gorrec, Yann Department of Automation and Micro-Mechatronic Systems FEMTO-ST UMR CNRS 6174 ENSMM 26 chemin de l'épitaphe F-25030 Besançon France University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Department of Applied Mathematics P.O. Box 217 7500 AE Enschede Netherlands

ISBN: (纸本)9783902823540

In this paper it is shown that an input strictly passive linear finite dimensional port-Hamiltonian controller exponentially stabilizes a large class of boundary control systems. This follows since the finite dimensional controller dissipates the energy flowing through the boundaries of the infinite dimensional system. The assumptions on the controller is that it is input strictly passive and that it is exponentially stable. The result is illustrated on the model of a boundary controlled DNA-manipulation process. © IFAC.

关键词： Controllers

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Efficient data-intensive processing in cloud computing environment

Efficient data-intensive processing in cloud computing envir...

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2013 International Conference on Communication Technology (ICCT 2013)

作者： Jiaman Ding Yi Du Qingxin Wang Ying Jiang Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and AutomationKunming University of Science and Technology City College Kunming University of Science and Technology

In order to solve the efficiency problem about the data-intensive query join in cloud computing environment, a Shrink-Semis Join for Cloud Computing(SSJFCC) method for data-intensive was proposed. This paper firstly analyzed and compared the bottlenecks of existing query join algorithm in the cloud computing environment. Secondly, aiming to shrink semi-results data from join process, five algorithms of SSJFCC method were designed. Finally, the improvement method had been implemented based on Hadoop framework. Experiments show that this method significantly reduced the network transmission data quantity and join computing time-consuming, and improved the data-intensive query efficiency.

关键词： data-intensive cloud computing query join map reduce

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Very short term pitch angle optimization in wind turbines: A machine learning approach

Very short term pitch angle optimization in wind turbines: A...

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International Conference on Power engineering, Energy and Electrical Drives, POWERENG

作者： Mehmet Yesilbudak Ersan Kabalci Seref Sagiroglu Ilhami Colak Department of Electronics and Automation Vocational College of Haci Bektas Veli Nevsehir University Nevsehir Turkey Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Nevsehir University Nevsehir Turkey Department of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey Department of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Turkey

This paper proposes a pitch angle forecasting model based on the k-nearest neighbor classification. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters were represented as a 6-dimensional attribute tuple in the forecasting model. Euclidean, Manhattan and Minkowski distance metrics for measuring the proximity between training and test tuples, mean absolute, mean absolute percentage, and normalized root mean square error metrics for measuring the forecasting accuracy were embedded into the forecasting model. The k-nearest neighbor classifier with Manhattan distance metric for k=1 achieved MAE, MAPE and NRMSE as 0.001°, 0.245% and 0.324%, respectively as the best forecasting accuracy. However, as the worst forecasting accuracy, MAE, MAPE and NRMSE were achieved as 0.015°, 3.236% and 2.613%, respectively for Minkowski distance metric and k=10.

关键词： Forecasting Measurement Wind turbines Predictive models Wind speed Atmospheric modeling Control systems

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Nonlinear analysis of dynamical complex networks 2014

Abstract and Applied Analysis

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Abstract and Applied Analysis 2014年第SI42期2014卷 1-4页

作者： Wang, Zidong Shen, Bo Dong, Hongli Hu, Jun He, Xiao Ding, Derui Department of Computer Science Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Communication Systems and Networks (CSN) Research Group Faculty of Engineering King Abdulaziz University Jeddah 21589 Saudi Arabia School of Information Science and Technology Donghua University Shanghai 200051 China College of Electrical and Information Engineering Northeast Petroleum University Daqing 163318 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin 150001 China Department of Applied Mathematics Harbin University of Science and Technology Harbin 150080 China Department of Automation Tsinghua University Beijing 100084 China Department of Applied Mathematics Anhui Polytechnic University Wuhu 241000 China

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Ensembles of echo state networks for time series prediction

Ensembles of echo state networks for time series prediction

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Wei Yao Zhigang Zeng Cheng Lian Huiming Tang School of Computer Science South-Central University for Nationalities Wuhan China School of Automation Huazhong University of Science and Technology Wuhan China Faculty of Engineering China University of Geosciences Wuhan China

In time series prediction tasks, dynamic models are less popular than static models, while they are more suitable for modeling the underlying dynamics of time series. In this paper, a novel architecture and supervised learning principle for recurrent neural networks, namely echo state networks, are adopted to build dynamic time series predictors. Ensemble techniques are employed to overcome the randomness and instability of echo state predictors, and a dynamic ensemble predictor is therefore established. The proposed predictor is tested in numerical experiments and different strategies for training the predictor are also comparatively studied. A case study is then conducted to test the predictor's performance in realistic prediction tasks.

关键词： Artificial neural networks Training

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Application of PID retuning method for laboratory feedback control system incorporating FO dynamics

Application of PID retuning method for laboratory feedback c...

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International Carpathian Control Conference (ICCC)

作者： L'ubomír Dorčák Emmanuel Gonzalez Ján Terpák Ivo Petráš Juraj Valsa Monika Žecová Institute of Control and Informatization of Production Processes Faculty BERG Technical University of Košice Kosice Slovakia Center for Automation Research College of Computer Studies De La Salle University Manila Philippines Faculty of Electrical Engineering and Computer Science Brno University of Technology Brno Czech Republic

Real objects in general are fractional-order (FO) systems, although in some types of systems the order is very close to integer order (IO). Since major advances have been made in the theory and practice of the identification of FO controlled objects and in the design of FO controllers, it is possible to consider also the real order of the dynamical systems and consider more quality criterion while designing the FO controllers with more degrees of freedom compared to their IO counterparts. In this paper, we present an application of the retuning method to design and apply new FO controller for the existing laboratory feedback control system with no modifications in the internal architecture of the original feedback control system. Along with the mathematical description, presented are also simulation results.

关键词： Closed loop systems Feedback control Mathematical model Laboratories Educational institutions PD control

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Tracking performance and disturbance rejection of pneumatic actuator system

Tracking performance and disturbance rejection of pneumatic ...

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Asian Control Conference

作者： Sy Najib Sy Salim Z. H. Ismail M. F. Rahmat A. A. M. Faudzi N. H. Sunar Sharatul Izah Samsudin Department of Control Instrumentation and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Malaysia Department of Control and Mechatronic Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia Centre for Artificial Intelligence & Robotics (CAIRO) Universiti Teknologi Malaysia Kuala Lumpur Malaysia Department of Industrial Electronics Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Malaysia

This paper investigates several control strategies that potential to perform well in regulating and tracking set point of pneumatic actuator system and able to reject disturbance. The system consists of 5-port proportional valve with the dead-band flow and double rod cylinders that exhibit significant friction. Two control strategies of PID and NPID controllers with four different configurations with and without dead-zone compensators (DZC) are simulated. Three different input signals including step, sinusoidal and random waveforms are used to evaluate the performance of the proposed techniques. The effectiveness of NPID+DZC has been successfully demonstrated and proved through simulation and experimental studies.

关键词： Friction Pneumatic actuators Valves Simulation Pneumatic systems Force

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Dijkstra's Algorithm for Cyber Structures Analysis

Dijkstra's Algorithm for Cyber Structures Analysis

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International Conference on the Experience of Designing and Application of CAD Systems in Microelectronics

作者： Chumachenko Svetlana Gorobets Alexander Chugurov Ihor Scherbin Dmytriy Design Automation Department Computer Engineering Faculty Kharkov National University of Radioelectronics

A modified Dijkstra's algorithm to determine the average cost of interconnections in computing architecture for every pair of nodes is proposed. Verification of the criterion, when evaluating the effectiveness of ... 详细信息

ISBN: (纸本)9781467364614

关键词： computer structures Dijkstra's algorithm Topology of digital system components

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Displacement prediction of landslide based on PSOGSA-ELM with mixed kernel

Displacement prediction of landslide based on PSOGSA-ELM wit...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Cheng Lian Zhigang Zeng Wei Yao Huiming Tang School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry China School of Computer Science South-Central University for Nationalities Wuhan China Faculty of Engineering China University of Geosciences Wuhan China

The prediction of landslide displacement is essential for carrying out to improve the disaster warning system and reduce casualties and property losses. This study applies a novel neural network technique, extreme learning machine (ELM) with kernel function, to landslide displacement prediction problem. However, the generalization performance of ELM with kernel function depends closely on the kernel types and the kernel parameters. In this paper, we use a convex combination of Gaussian kernel function and polynomial kernel function in ELM, which may use these two types of kernel functions' advantages. In order to avoid blindness and inaccuracy in parameter selection, a novel hybrid optimization algorithm based on the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) is used to optimize the regularization parameter C, the Gaussian kernel parameter γ, the polynomial kernel parameter q and the mixing weight coefficient η. The performance of our model is verified through two case studies in Baishuihe landslide and Yuhuangge landslide.

关键词： Kernel Terrain factors Optimization Hazards Reservoirs Training Support vector machines

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