eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
1
10
10.22060/miscj.2017.12239.5021
1012
Decentralized Model Reference Adaptive Control of Large Scale Interconnected Systems with Time-Delays in States and Inputs
Seyed Hamid Hashemipour
c.e.hashemi@gmail.com
1
Nastaran Vasegh
n.vasegh@srttu.edu
2
Ali Khaki Sedigh
sedigh@kntu.ac.ir
3
هیات علمی- دانشگاه آزاد اسلامی واحد رودسر و املش
هیات علمی- دانشگاه تربیت دبیر شهید رجایی
هیات علمی- دانشگاه صنعتی خواجه نصیر
This paper investigates the problem of decentralized model reference adaptive control (MRAC) for a class of large scale systems with time varying delays in interconnected terms and state and input delays. The upper bounds of the interconnection terms are considered to be unknown. Time varying delays in the nonlinear interconnection terms are bounded and nonnegative continuous functions and their derivatives are not necessarily less than one. Moreover, a simple and practical method based on periodic characteristics of reference model is established to predict the future states and input delay compensation. It is shown that the solutions of uncertain large-scale time-delay interconnected system converge uniformly exponentially to a desired small ball. The effectiveness of the proposed approaches are illustrated by a numerical example and a chemical reactor system.
http://miscj.aut.ac.ir/article_1012_d41d8cd98f00b204e9800998ecf8427e.pdf
Interconnected system
MRAC
State and input delays
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
11
20
10.22060/miscj.2017.12483.5036
1013
Integration Scheme for SINS/GPS System Based on Vertical Channel Decomposition and In-Motion Alignment
Hossein Nourmohammadi
hnourmohammadi@tabrizu.ac.ir
1
jafar keighobadi
keighobadi@tabrizu.ac.ir
2
University of Tabriz
Faculty of Mechanical Eng. University of Tabriz
Accurate alignment and vertical channel instability play an important role in the strap-down inertial navigation system (SINS), especially in the case that precise navigation has to be achieved over long periods of time. Due to poor initialization as well as the cumulative errors of low-cost inertial measurement units (IMUs), initial alignment is not sufficient to achieve required navigation accuracy. Concerning this problem, in the paper, misalignment error is dynamically modeled and in-motion alignment is provided based on position and velocity matching. It is revealed that, using misalignment error, orientation estimation can be properly corrected. Moreover, to prevent the instability effects of the vertical channel, decomposed SINS error model is derived. In the decomposed SINS error model, the navigation states in the vertical channel are separated from those in the horizontal plane. Two-step estimation process is developed for the integration of the aforementioned SINS error dynamics with the measurements provided by global positioning system (GPS) and fifteen-state SINS/GPS mechanization is presented. The assessment of the proposed approach is conducted in airborne test.
http://miscj.aut.ac.ir/article_1013_d41d8cd98f00b204e9800998ecf8427e.pdf
Low-cost Navigation
SINS/GPS Algorithm
In-Motion Alignment
Vertical Channel Decomposition
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
21
30
10.22060/miscj.2017.12188.5013
1014
Design of Observer-based H∞ Controller for Robust Stabilization of Networked Systems Using Switched Lyapunov Functions
Arash Farnam
arash.farnam@ugent.be
1
Reza Mahboobi Esfanjani
mahboobi@sut.ac.ir
2
SYSTeMS Research Group, Ghent University
Electrical Engineering Department, Sahand University of Technology
In this paper, H∞ controller is synthesized for networked systems subject to random transmission delays with known upper bound and different occurrence probabilities in the both of feedback (sensor to controller) and forward (controller to actuator) channels. A remote observer is employed to improve the performance of the system by computing non-delayed estimates of the sates. The closed-loop system is described in the framework of switched systems; then, a switched Lyapunov function is utilized to obtain conditions to determine the gains of the observer and controller such that robust asymptotic stability of the system is assured. Two illustrative examples are presented to demonstrate the real-world applicability and superiority of the proposed approach compared to some rival ones in the literature.
http://miscj.aut.ac.ir/article_1014_d41d8cd98f00b204e9800998ecf8427e.pdf
Networked Control System
H∞ controller
State observer
Random delays
Switched Lyapunov functions
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
31
40
10.22060/miscj.2017.12174.5008
1340
Robust adaptive control of voltage saturated flexible joint robots with experimental evaluations
Alireza Izadbakhsh
izadbakhsh_alireza@hotmail.com
1
Department of Electrical Engineering, Garmsar branch, Islamic Azad University, Garmsar, Iran
This paper is concerned with the problem of design and implementation a robust adaptive control strategy for flexible joint electrically driven robots (FJEDR), while considering to the constraints on the actuator voltage input. The control design procedure is based on function approximation technique, to avoid saturation besides being robust against both structured and unstructured uncertainties associated with external disturbances and un-modeled-dynamics. Stability proof of the overall closed-loop system is given via the Lyapunov direct method. The analytical studies as well as experimental results produced using MATLAB/SIMULINK external mode control on a single-link flexible joint electrically driven robot demonstrate high performance of the proposed control schemes.
http://miscj.aut.ac.ir/article_1340_d41d8cd98f00b204e9800998ecf8427e.pdf
Robust Adaptive Control
real-time Implementation
Actuator saturation
Function approximation technique
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
41
50
10.22060/miscj.2017.12236.5020
2667
An Efficient Data Replication Strategy in Large-Scale Data Grid Environments Based on Availability and Popularity
najme mansouri
najme.mansouri@gmail.com
1
Mohammad Javidi
javid@uk.ac.ir
2
Shahid Bahonar University of Kerman
Shahid Bahonar University of Kerman
The data grid technology, which uses the scale of the Internet to solve storage limitation for the huge amount of data, has become one of the hot research topics. Recently, data replication strategies have been widely employed in distributed environment to copy frequently accessed data in suitable sites. The primary purposes are shortening distance of file transmission and achieving files from nearby locations to requested sites so as to minimize retrieval time and bandwidth usage. In this paper, we propose a new replica selection strategy, which based on response time and security. However, replication should be used wisely because the storage size of each Data Grid site is limited. We also present a new replica replacement strategy based on the availability of the file, the last time the replica was requested, number of access, and size of replica. The simulation results report that the proposed strategy can effectively improve mean job time, bandwidth consumption for data delivery, and data availability as compared with those of the tested algorithms.
http://miscj.aut.ac.ir/article_2667_d41d8cd98f00b204e9800998ecf8427e.pdf
Data Grid
Dynamic Replication
File access pattern
Job Scheduling
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
51
60
10.22060/miscj.2017.12805.5043
2668
Dynamic Sliding Mode Control of Nonlinear Systems Using Neural Networks
Ali Karami-Mollaee
a_k_mollaee@yahoo.com
1
Hasan Shanechi
shanechi@iit.edu
2
Hakim Sabzevari University
Electrical and Computer Engineering Department, Illinois Institute of Technology, Chicago, USA
Dynamic sliding mode control (DSMC) of nonlinear systems using neural networks is proposed. In DSMC the chattering is removed due to the integrator which is placed before the input control signal of the plant. However, in DSMC the augmented system is one dimension bigger than the actual system i.e. the states number of augmented system is more than the actual system and then to control of such a system, we must to know and to identify the new states or the plant model should be completely known. To solve this problem, we suggest two online neural networks to identify and to obtain a model for the unknown nonlinear system. In the first approach, the neural network training law is based on the available system states and the bound of observer error is not proved to converge to zero. The advantageous of the second training law is only using of the system output and the observer error converges to zero based on the Lyapunov stability theorem. To verify these approaches Duffing-Holmes chaotic systems (DHC) is used.
http://miscj.aut.ac.ir/article_2668_d41d8cd98f00b204e9800998ecf8427e.pdf
Dynamic Sliding Mode Control
Neural Model
Nonlinear system
Duffing-Holmes Chaotic System
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
61
70
10.22060/miscj.2018.13020.5055
2828
Kinematic and Dynamic Analysis of Tripteron, an Over-constrained 3-DOF Translational Parallel Manipulator, Through Newton-Euler Approach
Alaleh Arian
aarian@ut.ac.ir
1
Behzad Danaei
behzad.danaei@gmail.com
2
Mehdi Tale Masouleh
m.t.masouleh@ut.ac.ir
3
Human and Robot Interaction Laboratory, Faculty of new sciences and Technologies, University of Tehran
Human and Robot Interaction Laboratory, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran
Human and Robot Interaction Laboratory, Faculty of New Sciences and Technologies, University of Tehran
In this research, as the main contribution, a comprehensive study is carried out on the mathematical modeling and analysis of the inverse kinematics and dynamics of an over-constraint three translational degree-of-freedom parallel manipulator. Due to the inconsistency between the number of equations and unknowns, the problem of obtaining the constraint forces and torques of an over-constraint manipulators do not admit solution, which can be regarded as one of the drawbacks of such mechanisms. In this paper, in order to overcome this problem and circumvent the inconsistency between the number of equations and unknowns, for the under study mechanism, two of the revolute joints attached to the end-effector are changed into a universal and a spherical joint without changing the motion pattern of the manipulator under study. Then, the dynamical equations of the manipulator are obtained based on the Newton–Euler approach and a simple and compact formulation is provided and all the joint forces and torques are presented. In order to evaluate the accuracy of the obtained formulated model, a motion for the end-effector as case study is performed, and it has been shown that the results of the analytical model are in good agreement with those obtained from SimMechanics model. Finally, the Root Mean Square Error is calculated between the analytical model and the results obtained from the simulation and experimental study.
http://miscj.aut.ac.ir/article_2828_d41d8cd98f00b204e9800998ecf8427e.pdf
Decoupled parallel manipulator
Dynamic Analysis
Kinematic analysis
Over-constraint manipulator
Newton–Euler approach
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
71
80
10.22060/miscj.2018.13473.5073
2834
Presenting a model for Multiple-step-ahead-Forecasting of volatility and Conditional Value at Risk in fossil energy markets
Ehsan Mohammadian Amiri
emohammadian@email.kntu.ac.ir
1
Seyed Babak Ebrahimi
b_ebrahimi@kntu.ac.ir
2
Faculty Of Industrial Engineering, K.N.Toosi University Of Technology,Tehran
Faculty Of Industrial Engineering, K.N.Toosi University Of Technology, Tehran, Iran,
Fossil energy markets have always been known as strategic and important markets. They have a significant impact on the macro economy and financial markets of the world. The nature of these markets are accompanied by sudden shocks and volatility in the prices. Therefore, they must be controlled and forecasted by using appropriate tools. This paper adopts the Generalized Auto Regressive Conditional Heteroskedasticity (GARCH)-type models, Exponential Smoothing (ES)-type models, and classic model in order to multiple-step-ahead forecast volatility, Value at Risk, and Conditional Value at Risk of Brent oil and natural gas in two different estimation window lengths, respectively. To evaluate the accuracy of the aforementioned models, eight different loss functions are utilized. The results show that, across all forecasting horizons and subsamples used, the Holt-Winters Exponential Smoothing (HWES) model, in comparison with GARCH-type models and classic model, provides more accurate forecasting of the volatility, Value at Risk, and Conditional Value at Risk, respectively. Therefore, the HWES model is proposed to multiple-step-ahead forecast these measures in fossil energy markets.
http://miscj.aut.ac.ir/article_2834_d41d8cd98f00b204e9800998ecf8427e.pdf
Multiple-step-ahead Forecasting
Volatility
Value at Risk
Conditional Value at Risk
ES models
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
81
90
10.22060/miscj.2017.12907.5048
2669
مقاله مروری
Adaptive attitude controller of a reentry vehicles based on Back-stepping Dynamic inversion method
abdollah mohseni
abdollah.mohseni@aut.ac.ir
1
farhad fani saberi
f.sabery@aut.ac.ir
2
mehdi mortazavi
mortazavi@aut.ac.ir
3
Aerospace department, Amirkabir university of technology, tehran, iran
Amirkabir university of technology
Aerospace department, Amirkabir university of technology, tehran, iran
This paper presents an attitude control algorithm for a Reusable Launch Vehicle (RLV) with a low lift/drag ratio (L/D < 0.5), in the presence of external disturbances, model uncertainties, control output constraints and the thruster model. The main novelty of proposed control strategy is a new combination of the attitude control methods included backstepping, dynamic inversion and adaptive control methods which will be called Backstepping-Dynamic inversion-Adaptive (B.D.A) method. In the proposed method, a single control variable is considered as the bank angle, while the angle of the attack and the side slip angle will be stabilized in the inherent value. The purpose of this control is the attitude control of the vehicle to track the commanded bank angle and keep the vehicle in the desired trajectory. Lyapunove stability analysis of the closed loop system will be performed to guaranty the stability of the vehicle in the presence of the considered constraint. The control performance will be evaluated based on six degrees of Freedom (6DOF) model of the reentry capsule. Also the results of the proposed control algorithm will be compared with the Backstepping-Dynamic inversion (B.D) control method.
http://miscj.aut.ac.ir/article_2669_d41d8cd98f00b204e9800998ecf8427e.pdf
Attitude control
Backstepping-Dynamic inversion-Adaptive
Reusable Launch Vehicle (RLV)
Controller output constraint
Thruster model
eng
Amirkabir University of Technology
AUT Journal of Modeling and Simulation
2588-2953
2588-2961
2018-06-01
50
1
91
100
10.22060/miscj.2018.13508.5074
2827
Forecasting Gold Price Changes: Application of an Equipped Artificial Neural Network
Reza Hafezi
r.hafezi@aut.ac.ir
1
Amir Akhavan
akhavan@aut.ac.ir
2
Technology Foresight Group, Department of Management, Science and Technology, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Technology Foresight Group, Department of Management, Science and Technology, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm decisions. This paper attempts to propose an intelligent model founded by artificial neural networks (ANNs) to project future prices of gold. The proposed intelligent network is equipped with a meta-heuristic algorithm called BAT algorithm to make ANN capable of following fluctuations. The designed model is compared to that of a published scientific paper and other competitive models such as Autoregressive Integrated Moving Average (ARIMA), ANN, Adaptive Neuro-Fuzzy Inference System (ANFIS), Multilayer Perceptron (MLP) Neural Network, Radial Basis Function (RBF) Neural Network and Generalized Regression Neural Networks (GRNN). In order to evaluate model performance, Root Mean Squared Error (RMSE) was employed as an error index. Results showed that the proposed BAT-Neural Network (BNN) outperforms both traditional and modern forecasting models.
http://miscj.aut.ac.ir/article_2827_d41d8cd98f00b204e9800998ecf8427e.pdf
Forecasting
Gold Price Fluctuations
Artificial Intelligence
Neural Network
BAT Algorithm