2013
45
1
1
0
Robust Fuzzy GainScheduled Control of the 3Phase IPMSM
Robust Fuzzy GainScheduled Control of the 3Phase IPMSM
2
2
This article presents a fuzzy robust Mixed  Sensitivity Gain  Scheduled H controller based on the Loop Shaping methodology for a class of MIMO uncertain nonlinear Time  Varying systems. In order to design this controller, the nonlinear parameter  dependent plant is first modeled as a set of linear subsystems by Takagi and Sugeno’s (T  S) fuzzy approach. Both Loop  Shaping methodology and Mixed  Sensitivity problem are then introduced to formulate the frequency  domain specifications. Furthermore, a Regular Weights Selection Method (RWSM) is used to devise a systematic design for choosing properly the weighting matrices. Afterwards, for each linear subsystem, an H∞∞ controller is designed via linear matrix inequality (LMI) approach. Such controllers are said to be scheduled by the Time  Varying parameter measurements in real time. The Parallel Distributed Compensation (PDC) is then used to design the controller for the overall system and the total linear system is also obtained through using the weighted sum of the local linear subsystems. Several results show that the proposed method can effectively meet the performance requirements like robustness, good load disturbance rejection and tracking responses, and fast transient responses for the 3  phase interior permanent magnet synchronous motor (IPMSM). Finally, the superiority of the proposed control scheme is approved in comparison with the feedback linearization controller, the H2/H∞ Controller and the H∞ Mixed  Sensitivity controller methods.
1
This article presents a fuzzy robust Mixed  Sensitivity Gain  Scheduled H controller based on the Loop Shaping methodology for a class of MIMO uncertain nonlinear Time  Varying systems. In order to design this controller, the nonlinear parameter  dependent plant is first modeled as a set of linear subsystems by Takagi and Sugeno’s (T  S) fuzzy approach. Both Loop  Shaping methodology and Mixed  Sensitivity problem are then introduced to formulate the frequency  domain specifications. Furthermore, a Regular Weights Selection Method (RWSM) is used to devise a systematic design for choosing properly the weighting matrices. Afterwards, for each linear subsystem, an H∞∞ controller is designed via linear matrix inequality (LMI) approach. Such controllers are said to be scheduled by the Time  Varying parameter measurements in real time. The Parallel Distributed Compensation (PDC) is then used to design the controller for the overall system and the total linear system is also obtained through using the weighted sum of the local linear subsystems. Several results show that the proposed method can effectively meet the performance requirements like robustness, good load disturbance rejection and tracking responses, and fast transient responses for the 3  phase interior permanent magnet synchronous motor (IPMSM). Finally, the superiority of the proposed control scheme is approved in comparison with the feedback linearization controller, the H2/H∞ Controller and the H∞ Mixed  Sensitivity controller methods.
1
14
V.
Azimi
V.
Azimi
Iran
M. B.
Menhaj
M. B.
Menhaj
Iran
A.
Fakharian
A.
Fakharian
Iran
Robust Control
T S Fuzzy Model
Gain  Scheduled Controller
Mixed Sensitivity Problem
Time Varying System
3 Phase Interior Permanent Magnet Synchronous Motor (IPMSM)
Exact Solution for Electro Thermo Mechanical Behavior of Composite Cylinder Reinforced by BNNTs under Non Axisymmetric Thermo Mechanical Loads
Exact Solution for Electro Thermo Mechanical Behavior of Composite Cylinder Reinforced by BNNTs under Non Axisymmetric Thermo Mechanical Loads
2
2
In this research, static stresses analysis of boron nitride nano  tube reinforced composite (BNNTRC) cylinder made of poly  vinylidene fluoride (PVDF) subjected to non  axisymmetric thermo  mechanical loads and applied voltage is developed. The surrounded elastic medium is modelled by Pasternak foundation. Composite structure is modeled based on piezoelectric fiber reinforced composite (PFRC) theory and a representative volume element has been considered for predicting the elastic, piezoelectric and dielectric properties of the cylinder. Higher order governing equations were solved analytically by Fourier series. The results demonstrated that the fatigue life of BNNTRC cylinder will be significantly dependent on the angle orientation and volume fraction of BNNTs. Results of this investigation can be used for the optimum design of thick  walled cylinders under the multi  physical fields.
1

15
25
A.
Ghorbanpour Arani
A.
Ghorbanpour Arani
Iran
E.
Haghparast
E.
Haghparast
Iran
Z.
Khoddami Maraghi
Z.
Khoddami Maraghi
Iran
S.
Amir
S.
Amir
Iran
Composite Hollow Cylinder
Non  Axisymmetric Temperature Distribution
PFRC Theory
Pasternak Foundation
BNNTs Fibers
Simulation of Singular Fourth Order Partial Differential Equations Using the Fourier Transform Combined With Variational Iteration Method
Simulation of Singular Fourth Order Partial Differential Equations Using the Fourier Transform Combined With Variational Iteration Method
2
2
In this paper, we present a comparative study between the modified variational iteration method (MVIM) and a hybrid of Fourier transform and variational iteration method (FTVIM). The study outlines the efficiencyand convergence of the two methods. The analysis is illustrated by investigating four singular partial differential equations with variable coefficients. The solution of singular partial differential equations usually needs a coordinate transformation in order to discard the singularity of the partial differential equation. Most often this transformation is not applicable and even does not exist. Therefore in this case the solution for the singular partial differential equation does not exist. In the present study the results of simulation for the singular partial differential equations with variable coefficients using the Fourier transform variational iteration method are compared with the results of simulation using the modified variational iteration method. The comparison shows that the effectiveness and accuracy of Fourier transform variational iteration method is more than that of the modified variational iteration method for the simulation of singular partial differential equations.
1
Robust Control؛ T S Fuzzy Model؛ Gain  Scheduled Controller؛ Mixed Sensitivity Problem؛ Time Varying System؛ 3 Phase Interior Permanent Magnet Synchronous Motor (IPMSM)
27
45
S. S.
Nourazar
S. S.
Nourazar
Iran
H.
Tamim
H.
Tamim
Iran
S.
Khalili
S.
Khalili
Iran
A.
Mohammadzadeh
A.
Mohammadzadeh
Iran
Fourier Transformation Modified Variational Iteration Method
Hybrid of Fourier Transform
Variational Iteration Method
Singular Partial Differential Equations With Variable Coefficients
Using the Adaptive Frequency Nonlinear Oscillator for Earning an Energy Efficient Motion Pattern in a Leg Like Stretchable Pendulum by Exploiting the Resonant Mode
Using the Adaptive Frequency Nonlinear Oscillator for Earning an Energy Efficient Motion Pattern in a Leg Like Stretchable Pendulum by Exploiting the Resonant Mode
2
2
In this paper we investigate a biological framework to generate and adapt a motion pattern so that can be energy efficient. In fact, the motion pattern in legged animals and human emerges among interaction between a central pattern generator neural network called CPG and the musculoskeletal system. Here, we model this neuro  musculoskeletal system by means of a leg  like mechanical system called stretchable pendulum, and an adaptive frequency nonlinear oscillator as a CPG unit. The stretchable pendulum is a simple oscillating mass  spring mechanism that interacts with the ground during its oscillations, and this interaction begins with a collision. Interaction with the ground causes the model to involve in two dynamic phases that are switched to each other through transition events. This hybrid model is very similar to models have been proposed for the legged locomotion mechanisms. Then, it will be simulated in coupling with an adaptive frequency Hopf oscillator as a controller placed in feedback loop. The simulation results reveal that this scheme is able to excite the mechanical system in an energy efficient pattern by way of exploiting resonance phenomenon. Also, adaptation of the system against the environmental changes is examined and it is seen that the controller is able to find the resonant mode after the changes were made.
1
In this paper we investigate a biological framework to generate and adapt a motion pattern so that can be energy efficient. In fact, the motion pattern in legged animals and human emerges among interaction between a central pattern generator neural network called CPG and the musculoskeletal system. Here, we model this neuro  musculoskeletal system by means of a leg  like mechanical system called stretchable pendulum, and an adaptive frequency nonlinear oscillator as a CPG unit. The stretchable pendulum is a simple oscillating mass  spring mechanism that interacts with the ground during its oscillations, and this interaction begins with a collision. Interaction with the ground causes the model to involve in two dynamic phases that are switched to each other through transition events. This hybrid model is very similar to models have been proposed for the legged locomotion mechanisms. Then, it will be simulated in coupling with an adaptive frequency Hopf oscillator as a controller placed in feedback loop. The simulation results reveal that this scheme is able to excite the mechanical system in an energy efficient pattern by way of exploiting resonance phenomenon. Also, adaptation of the system against the environmental changes is examined and it is seen that the controller is able to find the resonant mode after the changes were made.
47
54
Adaptive Frequency Oscillator
Central pattern Generator
Stretchable Pendulum
Legged Locomotion
Robust Model Based Fault Detection and Isolation for V47/660kW Wind Turbine
Robust Model Based Fault Detection and Isolation for V47/660kW Wind Turbine
2
2
In this paper, in order to increase the efficiency, to reduce the cost and to prevent the failures of wind turbines, which lead to an extensive break down, a robust fault diagnosis system is proposed for V47/660kW wind turbine operated in Manjil wind farm, Gilan province, Iran. According to the acquired data from Iran wind turbine industry, common faults of the wind turbine such as sensor faults, actuator faults and component faults are identified and considered in Fault Detection and Isolation (FDI) system design. Various Faults in abrupt and incipient natures can be detected and isolated using the indicators of faults, namely residuals, that are derived based on Unknown Input Observer (UIO) approach. Moreover, some thresholds are exploited to evaluate the produced residuals. The robustness of the proposed method against parameter uncertainties is shown as well. Simulations are performed in Matlab/Simulink environment to demonstrate the effectiveness of the proposed method using the actual parameters derived from the turbine model.
1
In this paper, in order to increase the efficiency, to reduce the cost and to prevent the failures of wind turbines, which lead to an extensive break down, a robust fault diagnosis system is proposed for V47/660kW wind turbine operated in Manjil wind farm, Gilan province, Iran. According to the acquired data from Iran wind turbine industry, common faults of the wind turbine such as sensor faults, actuator faults and component faults are identified and considered in Fault Detection and Isolation (FDI) system design. Various Faults in abrupt and incipient natures can be detected and isolated using the indicators of faults, namely residuals, that are derived based on Unknown Input Observer (UIO) approach. Moreover, some thresholds are exploited to evaluate the produced residuals. The robustness of the proposed method against parameter uncertainties is shown as well. Simulations are performed in Matlab/Simulink environment to demonstrate the effectiveness of the proposed method using the actual parameters derived from the turbine model.
55
66
Sh.
Asgari
Sh.
Asgari
Iran
A.
Yazdizadeh
A.
Yazdizadeh
Iran
M. G.
Kazemi
M. G.
Kazemi
Iran
Fault Detection and Isolation(FDI)
Renewable Energy
Robust
Unknown Input Observer (UIO)
Wind Turbine
A Stock Market Filtering Model Based on Minimum Spanning Tree in Financial Networks
A Stock Market Filtering Model Based on Minimum Spanning Tree in Financial Networks
2
2
There have been several efforts in the literature to extract as much information as possible from the financial networks. Most of the research has been concerned about the hierarchical structures, clustering, topology and also the behavior of the market network; but not a notable work on the network filtration exists. This paper proposes a stock market filtering model using the correlation  based financial networks in which network nodes represent the potential stocks and network edges indicate the correlation coefficients of corresponding stock pairs. The model is capable of reducing the basic market size while keeping the diversification and risk  return expectations fairly constant. The novelty of this research is to develop a new market network filtering method which exploits Minimum Spanning Tree (MST) to reduce the number of network nodes (graph order) rather than the links (graph size). The proposed method chooses the nodes (stocks) based on dangling ends of the constructed MST. In order to verify our proposed model, we applied the model on data of three stock markets: New York Stock Exchange (NYSE), Germany Stock Exchange (DAX) and Toronto Stock Exchange (TSE). In conclusion, the numerical results showed that our proposed model can make a subset of the stock market in which its performance can imitate the whole market with a rather considerable reduction in size; as a result, we can have a diversified subset of the market compatible with that of the whole market. The performance of the model is confirmed by comparing the portfolio of the filtered market network with the whole market portfolio using the complement of Herfindahl Index as a measure of diversification.
1
There have been several efforts in the literature to extract as much information as possible from the financial networks. Most of the research has been concerned about the hierarchical structures, clustering, topology and also the behavior of the market network; but not a notable work on the network filtration exists. This paper proposes a stock market filtering model using the correlation  based financial networks in which network nodes represent the potential stocks and network edges indicate the correlation coefficients of corresponding stock pairs. The model is capable of reducing the basic market size while keeping the diversification and risk  return expectations fairly constant. The novelty of this research is to develop a new market network filtering method which exploits Minimum Spanning Tree (MST) to reduce the number of network nodes (graph order) rather than the links (graph size). The proposed method chooses the nodes (stocks) based on dangling ends of the constructed MST. In order to verify our proposed model, we applied the model on data of three stock markets: New York Stock Exchange (NYSE), Germany Stock Exchange (DAX) and Toronto Stock Exchange (TSE). In conclusion, the numerical results showed that our proposed model can make a subset of the stock market in which its performance can imitate the whole market with a rather considerable reduction in size; as a result, we can have a diversified subset of the market compatible with that of the whole market. The performance of the model is confirmed by comparing the portfolio of the filtered market network with the whole market portfolio using the complement of Herfindahl Index as a measure of diversification.
67
75
A.
Esfahanipour
A.
Esfahanipour
Iran
S. E.
Zamanzadeh
S. E.
Zamanzadeh
Iran
Stock Market Filtering
Financial Networks
Minimum Spanning Tree (MST)
Markowitz’s Mean  Variance Method
Diversification