per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2012-09
6
2
1
13
article
An Active Approach to Model-based Fault Tolerant Control System Design for Three Phase Induction Motors
Hamed Rezaei
rezaei.hamed1@gmail.com
1
Mohammad Javad Khosrowjerdi
khosrowjerdi@sut.ac.ir
2
In this paper, a model-based active fault tolerant control system (FTCs) is proposed forthree phase induction motor (IM) drives subjected to the mechanical faults caused by both stator and rotor failures. FTCsstructure consists of two main parts. The first part is a nominal controller based on feedback linearization for fault-free case to achieve control objectives (rotor flux and speed control). The second part is a sliding mode observer (SMO) in order to estimate additive faults which model mechanical faults in the state space modelof IM. This observer has been used not only for fault reconstruction and productionof additional control inputs for compensating their undesirable influences on performance of IM, but also for online estimation of axial fluxes in any operating conditions. The simulations results are shown to illustrate the effectiveness of the proposed approach to compensate the mechanical faults in IM.
http://joc.kntu.ac.ir/article-1-56-en.pdf
Induction Motor (IM)
Mechanical Fault
Fault Tolerant Control system (FTCs)
Fault Detection and Isolation (FDI)
Sliding Mode Observer (SMO).
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2012-09
6
2
15
21
article
Performance Analysis of Nasir 1 Star Tracker in the Presence of Systematic Errors using Monte-Carlo Method
Jafar Roshanian
roshanian@kntu.ac.ir
1
Shabnam Yazdani
Syazdani@kntu.ac.ir
2
Mehdi Hassani
smh1384@gmail.com
3
Masoud Ebrahimi
ebrahimi_k_m@yahoo.co
4
Non-Dimensional star pattern recognition is a novel algorithm which an overall system error analysis in order to determine its robustness is not performed for it so far. Although the mentioned algorithm is independent of Focal length and optical offset variations, its operational usage is still bounded. In this research, algorithm’s robustness is determined using an overall error effect of bright point coordinate variations. The results demonstrate that the non-dimensional algorithm performance is pretty fragile in the presence of a common 0.1 pixel error, which makes the algorithm unable to perform onboard Nasir 1 star tracker. Eventually the algorithm was modified and the results show great improvements.
http://joc.kntu.ac.ir/article-1-57-en.html
Star Tracker
Star Pattern Recognition
Non-Dimensional method
K-vector search technique.
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2012-09
6
2
23
37
article
Inverse Kinematics of 7 DOF Robot Manipulator under Joint Angle Limits and Obstacle in the Workspace of Robot using Neural network, Fuzzy System and Quadratic Programming Approach
Hamid Toshani
h_toshany@yahoo.com
1
Mohammad Farrokhi
farrokhi@iust.ac.ir
2
Analysis of the inverse kinematics of redundant manipulators is one of the nesseccary tools in various robotic fields such as design, motion planning and control of these systems. Since, there is not an analytical solution for the inverse kinematics of several redundant manipulators, numerical approaches are needed to execute and investigate in this field. In this paper, combination of the neural networks, fuzzy systems and quadratic programming is used to obtain the joint variables. According to the proposed approach, seven neural networks are considered according to the each joint variable and by adaptation of the neural network’s weights, suitable configurations of the robot is determined to track a desired trajectory in the Cartesian space. Meanwhile, initial weights of the neural networks are obtained by fuzzy systems based on the vicinity of the end-effector to desired point and feasibility of the joint variables. Obstacle avoidance scheme is performed by investigation of the conditions including choosing the joint variables that involved in the equations of the arms constraints and determination of the most critical arm. In order to establish the constraints of the problem in the quadratic programming, realization of the Kun-Tucker conditions will be used. Evaluation of the proposed approach will be carried out on the PA-10 manipulator by simulation and analysis of the results.
http://joc.kntu.ac.ir/article-1-58-en.pdf
Inverse Kinematics
Redundant Manipulator
Neural Network
Quadratic Progarmming
Fuzzy System
Obstacle Avoidance.
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2012-09
6
2
39
53
article
Control of a Manipulator with Elastic Base Moving on Unknown Path
Ali Salehi
asalehi@me.iut.ac.ir
1
Mohammad Jafar Sadigh
jafars@cc.iut.ac.ir
2
Cooperation of man and machine is one of the best solutions for moving the end-effector of a manipulator on a specific path with unknown relation. In such a solution deviation from the path is assessed by operator and necessary correcting command is generated by him based on that. This navigation command is, then, used by control algorithm of manipulator to move the end-effector on the desired path. This problem gets more difficult if the base of manipulator is moving on a platform such as a cart or a large manipulator, with inherent flexibility, to achieve a large workspace. In such cases it is impossible to use a master similar to the manipulator itself. This paper presents a fuzzy navigation algorithm for moving end-effector of a manipulator mounted on a moving base. The algorithm which is based on estimation of cross track error of end-effector, generates necessary command which is used by a proposed computed-torque method algorithm to move the end-effector on the desired path. Simulation results shows versatility of the proposed methods for navigation and control of the system even in presence of disturbances due to flexibility of base.
http://joc.kntu.ac.ir/article-1-59-en.pdf
Man and Machine Cooperation
Navigation
Unknown Path
Flexible Base Robot.
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2012-09
6
2
55
64
article
Three-Dimensional Optimal Robust Guidance Law Design for Missile Using Sliding-Mode Control and SDRE Control
Seyed Sajad Moosapour
Smoosapour@gmail.com
1
Ghasem Alizadeh
Alizadeh@tabrizu.ac.ir
2
Sohrab Khanmohammadi
Khan@tabrizu.ac.ir
3
In this paper, a new guidance law is designed for missile against maneuvering target by integrating optimal control SDRE technique and sliding-mode control. Due to the fact that autopilot dynamic has a very important role in success or unsuccess of engagement in terminal phase, and it can make delay in guidance commands execution, this dynamic is taken into account in state equations. The robustness of the designed guidance law against disturbances is proved by the second method of Lyapunov. The proposed guidance law does not need accurate target maneuver profile and just need the maximum value of the target maneuver. Coefficients in proposed guidance law are obtained using genetic algorithm. For investigating effectiveness of proposed guidance law, by considering different scenarios, three-dimensional missile-target engagement is simulated. Then results are compared with conventional augmented proportional navigation guidance (APNG) law. Simulation results show that the proposed guidance law has high robustness against target maneuver disturbances and also one can compromise between convergence speed, intercept time and control effort.
http://joc.kntu.ac.ir/article-1-60-en.pdf
Missile
guidance
optimal control
robust control
sliding-mode
genetic algorithm.
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2012-09
6
2
65
76
article
A Novel Approach to Robustness Analysis for the Solutions of the Games with Approximate Payoffs
Gelareh Veisi
gveisi@gmail.com
1
Rajab Asgharian
rajab.asgharian@gmail.com
2
When using game theory for modeling real- world problems, players' payoffs are usually known approximately. Literature reveals that some authors have modeled the approximate payoffs using stochastic or fuzzy variables and some others have used robust optimization techniques to solve these games. Surprisingly little work has been done on robustness analysis of real- world's games solutions.
In this paper, we propose two simple and practical measures to assess robustness degrees of Nash equilibria. These measures quantitatively show how Nash points behave in the presence of uncertainty and they can be used as refinements of Nash equilibrium. Also we propose two novel approaches to assess robustness degrees of correlated equilibria. One approach is a quantitative way to calculate robustness degrees and the other is a comparative measure to rank correlated equilibria in order of their robustness. We suggest that the decision maker may be able to find more robust solutions in the set of non- Nash correlated equilibria. Moreover, we present a method to improve robustness of Nash points. The improvement algorithm searches for more robust solutions in a neighborhood around a Nash point.We validate our methods with some numerical examples. The examples verify the efficiency of the methods.
http://joc.kntu.ac.ir/article-1-61-en.pdf
game theory
robust Nash point
robust correlated equilibrium
robustness analysis
payoff uncertainty
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2012-09
6
2
77
85
article
Decentralized Reduced Order Observer Design for Large-Scale Plants with Unknown Inputs
Bijan Moaveni
b_moaveni@iust.ac.ir
1
Mina Gholami
minagholamii@gmail.com
2
In this paper, we propose a new method to design a decentralized reduced order observer for large scale plants with unknown inputs. In this approach, large scale plant is decomposed into several subsystems with interconnected terms, then interconnected terms will be eliminated by using the appropriate transformations in new form of dynamical equation of each subsystem. Based on this method, states estimation doesn’t require exchanging information between the subsystems. Here, if plant satisfies the existence condition for designing stable observer with unknown input (UIO), we use estimation error dynamic and negative definite to provide the observer convergence. Finally, effectiveness of the method is shown by using a numerical example and corresponding simulation.
http://joc.kntu.ac.ir/article-1-62-en.pdf
Large Scale Plant
Decentralized Observer
Reduce Order Observer
Unknown Input Observer.