The 2nd International Conference on Control, Instrumentation and Automation最新文献_第10页

A graphical approach to design PI controller for integrator plus dead-time processes 积分器加死时过程PI控制器的图形化设计方法

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356677

I. Momenizadeh, A. Madady, H. Reza-Alikhani

{"title":"A graphical approach to design PI controller for integrator plus dead-time processes","authors":"I. Momenizadeh, A. Madady, H. Reza-Alikhani","doi":"10.1109/ICCIAUTOM.2011.6356677","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356677","url":null,"abstract":"The proportional-integral (PI) and proportional integral-derivative (PID) controllers are widely used in lots of industrial control systems for many years since Ziegler and Nichols proposed their first PID tuning scheme. This is because the PI/PID controller structure is simple and its principle is easier to understand than most other advanced controllers. The aim and the contribution of this paper is to develop a novel graphical method to design the PI controller for industrial processes which are modeled by an integrator plus dead time (IPDT) transfer function. For this purpose, a set of loci is developed and plotted in the controller parameters plane, which one of the quantities consists of gain and phase margins, gain and phase crossover frequencies and Smith's vector margin is constant on each locus. Next, the desired closed loop system characteristics are stated in the form of two loci. By sketching these two loci and obtaining their intersection point the controllers parameters are determined. Finally some examples are given to demonstrate the effectiveness of the proposed method.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125464719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Initial test and design of a soft sensor for flow estimation using vibration measurements 利用振动测量进行流量估计的软传感器的初步测试和设计

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356765

R. Safari, B. Tavassoli

引用次数: 6

A GOBF-wavelet wiener model for identification of nonlinear dynamic systems 一种用于非线性动力系统辨识的gbf -小波维纳模型

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356832

M. Salimifard, A. Safavi, M. Shaheed

引用次数: 0

Design of new soft sensors based on PCA, genetic algorithm and neural network for parameters estimation of a petroleum reservoir 基于PCA、遗传算法和神经网络的油气储层参数估计软传感器设计

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356768

H. Alaei

{"title":"Design of new soft sensors based on PCA, genetic algorithm and neural network for parameters estimation of a petroleum reservoir","authors":"H. Alaei","doi":"10.1109/ICCIAUTOM.2011.6356768","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356768","url":null,"abstract":"A new set of soft sensors is presented, based on principal component analysis (PCA), genetic algorithm (GA) and artificial neural network (ANN) methodologies for parameters estimation of a petroleum reservoir. The crude diagrams of reservoir parameters provide valuable evaluation for petro-physical parameters. These parameters, however, are usually difficult to measure due to limitations insights on cost, reliability considerations, inappropriate instrument maintenance and sensor failures. PCA and genetic algorithm is utilized to develop new soft sensors to incorporate reliability and prediction capabilities of ANN. Genetic algorithms are used to decide the initial weights of the gradient decent methods so that all the initial weights can be searched intelligently. The genetic operators and parameters are carefully designed and set avoiding premature convergence and permutation problems. The proposed algorithm combines the local searching ability of the gradient-based back-propagation (BP) strategy with the global searching ability of genetic algorithms in the PCA subspaces. The developed soft sensors are applied to reconstruct parameters of Marun reservoir located in Ahwaz, Iran, by utilizing the available geophysical well log data.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127229342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kinematic control of a seven DOF robot manipulator with joint limits and obstacle avoidance using neural networks 基于神经网络的关节限制和避障七自由度机器人的运动控制

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356794

H. Toshani, M. Farrokhi

{"title":"Kinematic control of a seven DOF robot manipulator with joint limits and obstacle avoidance using neural networks","authors":"H. Toshani, M. Farrokhi","doi":"10.1109/ICCIAUTOM.2011.6356794","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356794","url":null,"abstract":"In this paper, a numerical method based on neural network is presented to solve inverse kinematics problem of redundant manipulators subject to joint angle limits and obstacles in the workspace of the robot. The proposed method is performed in real time, where radial-basis function neural network is used to obtain joint angles of the robot. In order to satisfy constrains, a method called Nonlinear Quadratic Programming (NQP) is applied to update NN's weights. Moreover, it will be shown that if the Kuhn-Tucker conditions are satisfied, then convergence of NN's weights is guaranteed. Since the process is performed on-line, the computational time of obtaining the inverse kinematics solution must be suitable for real-time applications such as control of the robot manipulators. Moreover, since the convergence rate of the problem depends on the initial weights of the neural network, several initial weights are used relative to suitable factors such as feasibility of the solution and vicinity of the desired point. Simulations are carried out on the PA-10 redundant manipulator to show effectiveness of the proposed algorithm.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"819 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127591844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Bayesian networks design of load-frequency control based on GA 基于遗传算法的负载频率控制贝叶斯网络设计

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356676

Fatemeh Daneshfar, H. Bevrani, F. Mansoori

{"title":"Bayesian networks design of load-frequency control based on GA","authors":"Fatemeh Daneshfar, H. Bevrani, F. Mansoori","doi":"10.1109/ICCIAUTOM.2011.6356676","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356676","url":null,"abstract":"Frequency regulation in interconnected networks is one of the main challenges in power systems. Significant interconnection frequency deviations can cause under/over frequency relaying and disconnect some loads and generations. Under unfavorable conditions, this may result in a cascading failure and system collapse. A control strategy for solving this problem in a multi-area power system is presented by an intelligent based load frequency control (LFC) using Bayesian networks (BNs). This method admits considerable flexibility in defining the control objectives specifically in a large scale power system. The BNs provide efficient probabilistic inference algorithms that permit answering various probabilistic queries about the system and incorporate expert knowledge and historical data for revising the prior belief in the light of new evidence in many fields. It is also possible to include local conditional dependencies into the model, by directly specifying the causes that influence a given effect. To demonstrate the capability of the proposed control structure, a three-control area power system simulation with two different scenarios is presented.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121257160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Nonlinear PI controller for interior permanent magnet synchronous motor drive 内置永磁同步电机驱动的非线性PI控制器

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356660

M. Mardaneh, F. Bavafa, S. Alavi, M. Sadeghi

引用次数: 4

A fast convergence algorithm for BPNN based on optimal control theory based learning rate 基于最优控制理论的bp神经网络快速收敛算法

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356672

E. Zeraatkar, Mohammad Soltani, P. Karimaghaee

{"title":"A fast convergence algorithm for BPNN based on optimal control theory based learning rate","authors":"E. Zeraatkar, Mohammad Soltani, P. Karimaghaee","doi":"10.1109/ICCIAUTOM.2011.6356672","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356672","url":null,"abstract":"In this paper, a novel updating law for Backpropagation learning algorithm based on optimal control theory is proposed. The original Backpropagation algorithm composed of learning rate factor (LR). The coefficient in LR is called step size and indicates the rate of algorithm convergence which is selected by trial and error. In original BP the step size is constant. This fixed step size causes important incapabilities such as slow convergence and local minima problem. In Optimal Control Theory Based Learning Rate (OCLR)algorithm the step size is selected adaptively according to optimal control theory that makes Backpropagation learning algorithm convergence much faster than the original BP. To achieve the fastest possible answer, the Backpropagation learning algorithm is modeled as a minimum time control problem and the step size coefficient is considered as input. This consideration results a Bang-Bang control characteristics. The effectiveness of the proposed algorithm is evaluated via two examples. These examples are XOR, 3-bit parity. In all the problems, the proposed algorithm outperforms well in speed and the ability to escape from local minima.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115428008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A semi-analytic modeling of nonlinearities for nano-robotic applications, macro and micro sized systems 应用于纳米机器人、宏观和微观系统的非线性半解析建模

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356795

M. Korayem, A. Homayooni, S. Sadeghzadeh, M. Safa, V. Rahneshin

引用次数: 2

Flux and torque control of synchronous reluctance motor based on second order sliding mode method 基于二阶滑模方法的同步磁阻电机磁链和转矩控制

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356707

S. S. Boroujeni, G. Markadeh, J. Soltani, N. Abjadi

引用次数: 1