The 2nd International Conference on Control, Instrumentation and Automation最新文献_第5页

Power system stabilizer design using real-coded genetic algorithm 电力系统稳定器的实编码遗传算法设计

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356625

A. Ahmad, A. Abdelqader

{"title":"Power system stabilizer design using real-coded genetic algorithm","authors":"A. Ahmad, A. Abdelqader","doi":"10.1109/ICCIAUTOM.2011.6356625","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356625","url":null,"abstract":"Small-signal stability is a key element in the studies of dynamic performance of electric power systems. One of the main considerations in stability analysis is the low-frequency oscillations of rotor due to disturbances of which the power system is susceptible to. These oscillations may sustain and grow in magnitude to cause system separation if adequate damping is not provided, especially during using an AVR in the system. To enhance system damping, the generating unit is equipped with a power system stabilizer (PSS). Conventional PSS controllers are widely utilized in industry to damp the low-frequency inertial oscillations experienced due to disturbances. The design of such stabilizer encompasses finding the best settings of PSS parameters which yield the attainable damping response. Several design approaches and techniques have been proposed (i.e. sequential PSS design, Ha>; optimization technique, etc.) over the years. A novel genetic-algorithm (GA) based optimization approach to design a robust PSS is presented in this paper. This proposed approach employs optimization of damping factor (σ) and damping ratio () in parallel with speed deviation based performance index (IAE) optimization, to obtain the best possible time-domain results (minimum settling time, sserror, etc.). The well-known single-machine infinite bus system is used here. Simulation of the linearized system is presented. The system speed response is investigated with and without PSS. Their results are compared and show that the response of the system with PSS sustains its stability during system upsets, which means that the proposed method gives encouraging results compared with traditional methods.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"49 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":"120961333","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: 10

Microcontroller optimization of thermal characteristic in pezoresistive MEMS pressure sensors in height measurement in fuel reservoirs 油箱高度测量中压电式MEMS压力传感器热特性的微控制器优化

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356762

M. Salehi, E. Abiri, M. Jowkar

引用次数: 0

Reduced cubature Kalman filtering applied to target tracking 简化卡尔曼滤波在目标跟踪中的应用

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356814

D. Mohammed, M. Abdelkrim, K. Mokhtar, O. Abdelaziz

引用次数: 6

Neural autopilot predictive controller for nonholonomic wheeled mobile robot based on a pre-assigned posture identifier in the presence of disturbances 基于预分配姿态标识符的非完整轮式移动机器人神经自动驾驶预测控制器

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356678

A. Al-Araji, M. Abbod, H. Al-Raweshidy

{"title":"Neural autopilot predictive controller for nonholonomic wheeled mobile robot based on a pre-assigned posture identifier in the presence of disturbances","authors":"A. Al-Araji, M. Abbod, H. Al-Raweshidy","doi":"10.1109/ICCIAUTOM.2011.6356678","DOIUrl":"https://doi.org/10.1109/ICCIAUTOM.2011.6356678","url":null,"abstract":"This paper proposes an adaptive neural predictive controller to guide a nonholonomic wheeled mobile robot during continuous and non-continuous gradients trajectory tracking. The structure of the controller consists of two models that describe the kinematics and dynamics of the mobile robot system and a feedforward neural controller. The models are modified Elman neural network and feedforward multi-layer perceptron respectively. The trained Elman neural model acts as the position and orientation identifier. The feedforward neural controller is trained off-line and adaptive weights are adapted on-line to find the reference torques, which controls the steady-state outputs of the mobile robot system. The feedback neural controller is based on the posture neural identifier and quadratic performance index optimisation algorithm to find the optimal torque action in the transient state for N-step-ahead prediction. General back propagation algorithm is used to learn the feedforward neural controller and the posture neural identifier. Simulation results show the effectiveness of the proposed adaptive neural predictive control algorithm; this is demonstrated by the minimised tracking error and the smoothness of the torque control signal obtained with bounded external disturbances.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"23 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":"125261386","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: 5

Constrained model predictive control of PEM fuel cell with guaranteed stability 保稳定性PEM燃料电池的约束模型预测控制

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356654

S. Minagar, Reza Ghaderi, A. R. Noey

引用次数: 0

Hybrid model predictive control of legless piezo capsubot 无腿压电胶囊机器人的混合模型预测控制

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356788

S. Kalantari, A. A. Farahani, A. Doustmohammadi, M. Menhaj, A. Suratgar, H. Talebi

引用次数: 3

Low speed control of an autonomous vehicle using a hybrid fractional order controller 基于混合分数阶控制器的自动驾驶汽车低速控制

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356641

S. Hosseinnia, I. Tejado, B. Vinagre, V. Milanés, J. Villagrá

引用次数: 15

Kinematics analysis, dynamic modeling and verification of a CRRR 3-DOF spatial parallel robot CRRR三自由度空间并联机器人运动学分析、动力学建模与验证

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356809

A. Nazari, S. Moosavian, A. Hasani

引用次数: 2

Adjustable output voltage Zeta converter using neural network adaptive model reference control Zeta变换器输出电压可调采用神经网络自适应模型参考控制

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356718

B. Moaveni, H. Abdollahzadeh, M. Mazoochi

引用次数: 7

Nonlinear robust control of flexible-link manipulator with fuzzy compensator: Experimental results 基于模糊补偿的柔性臂非线性鲁棒控制:实验结果

The 2nd International Conference on Control, Instrumentation and Automation Pub Date : 2011-12-01 DOI: 10.1109/ICCIAUTOM.2011.6356797

H. Khorasgani, N. E. Ghiasi, A. Farshad, H. Talebi

引用次数: 4