per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2018-06
12
2
1
11
article
Calculation of Interactor Matrix for Nonlinear Multivariable Systems via Infinite Zero Structure Algorithm
Zeinab Aslipour
z_aslipour@sbu.ac.ir
1
Alireza Fatehi
fatehi@kntu.ac.ir
2
K.N. Toosi University of Technology
K.N. Toosi University of Technology
An interactor matrix plays an important role in the multivariable linear and nonlinear control systems theory. This paper proposes a method to obtain the interactor matrix for nonlinear multivariable systems. The only existing algorithm works only on square systems; moreover, it cannot guarantee providing the interactor matrix for these systems. The proposed method of this paper improves the above algorithm so that both mentioned defects are solved. The modified algorithm uses the infinite zeros structure for the nonlinear system and then it obtains the structure of interactor matrix. The effectiveness of the introduced method has been shown using various examples.
http://joc.kntu.ac.ir/article-1-460-en.html
Nonlinear System
Multi-Input Multi-Output
Interactor Matrix
Infinite Zeros Structure
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2018-06
12
2
13
25
article
Suboptimal Solution of Nonlinear Graphical Games Using Single Network Approximate Dynamic Programming
Majid Mazouchi
Mazouchi.Majid@stu.um.ac.ir
1
Mohammad Bagher Naghibi Sistani
Mb-naghibi@um.ac.ir
2
Seyed Kamal Hosseini Sani
k.hosseini@um.ac.ir
3
Ferdowsi University of Mashhad
Ferdowsi University of Mashhad
Ferdowsi University of Mashhad
In this paper, an online learning algorithm based on approximate dynamic programming is proposed to approximately solve the nonlinear continuous time differential graphical games with infinite horizon cost functions and known dynamics. In the proposed algorithm, every agent employs a critic neural network (NN) to approximate its optimal value and control policy and utilizes the proposed weight tuning laws to learn its critic NN optimal weights in an online fashion. Critic NN weight tuning laws containing a stabilizer switch guarantees the closed-loop system stability and the control policies convergence to the Nash equilibrium. In this algorithm, there is no requirement for any set of initial stabilizing control policies anymore. Furthermore, Lyapunov theory is employed to show uniform ultimate boundedness of the closedloop system. Finally, a simulation example is presented to illustrate the efficiency of the proposed algorithm.
http://joc.kntu.ac.ir/article-1-382-en.html
Approximate Dynamic Programming
Neural Networks
Optimal Control
Reinforcement learning
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2018-06
12
2
27
39
article
Designing an Output Feedback Tracking Controller for Mobile Manipulators by Using a Neural Adaptive Robust Technique
Nooshin Poorvaez
n.poorvaez@sel.iaun.ac.ir
1
Khoshnam Shojaei
shojaei@pel.iaun.ac.ir
2
Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
In this paper, the tracking control of a robotic arm mounted on a wheeled mobile platform is considered. A nonlinear neural adaptive robust control algorithm is proposed for the output feedback tracking control of a wheeled mobile manipulator without measuring system velocities to deal with the unmodeled system dynamics, parametric uncertainties and external disturbances. A Lyapunov-based stability analysis shows that tracking and observation errors are Uniformly Ultimately Bounded (UUB) and converge to a small ball containing the origin. A Radial Basis Function Neural Network (RBFNN) is employed to compensate for the uncertainties of mobile manipulator dynamics. Nonparametric uncertainties and NN approximation errors are also compensated by an adaptive robust controller. In addition, hyperbolic tangent function is employed in the design of the output feedback controller to reduce the risk of actuators saturation and to produce smoother control signals. Finally, simulation results demonstrate the effectiveness of the proposed controller well.
http://joc.kntu.ac.ir/article-1-489-en.html
Actuator saturation
Mobile manipulators
Nonlinear adaptive robust control
Radial basis function neural network.
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2018-06
12
2
41
51
article
Asynchronous Stochastic Controller Design for a Class of Markov Jump Linear Systems
Mona Faraji-Niri
m_farajiniri@pooyesh.ac.ir
1
Mohammad Reza Jahed Motlagh
jahedmr@iust.ac.ir
2
Pooyesh Institiute of Higher Education
Iran University of Science and Technology
This paper investigates asynchronous controller design problem for a class of continuous-time Markov jump linear systems. The mentioed asynchronous phenomenon is a case in which the system and the controller Markov chainsare not matched, however they are relevant according to certain probabilities. This phenomenon describes a realistic and practical situation which arises as a result of inaccurate observation of the system’s Markov chain. The proposed design scheme considers the closed-loop system as a unified Markov jump linear system and utulizes the multiple Lyapunov function approach. By this approach, firstly, the stabilizability of the closed-loop system is ensured and then the asynchronous state-feedback controller is synthesizesed. The designed controller is formulated in terms of linear matrix inequalities; which are easy to check. A numerical example illustrates the usefulness of the developed method.
http://joc.kntu.ac.ir/article-1-426-en.html
Asynchronous Control
Linear Matrix Inequality
Markov Jump Linear System
Stochastic Control.
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2018-06
12
2
53
66
article
Reduction in Number of Switching Elements of the Inverter Unit for the Proposed Dual Stator Winding Squirrel-Cage Induction Motor Speed Control Drive
Hojat Moayedirad
hojatrad@birjand.ac.ir
1
Mohammad Ali Shamsi Nejad
mshamsi@birjand.ac.ir
2
University of Birjand
University of Birjand
A dual stator winding induction motor (DSWIM) is a brushless squirrel-cage induction motor that contains a stator with two isolated three-phase windings wound with dissimilar number of poles. Generally, each stator winding is fed by an independent three-phase inverter. A direct vector control is a suitable method for controlling the DSWIM drive. In the vector control method, the estimation of the rotor flux is difficult at low speeds. In this paper, a direct vector control is proposed based on the rotor flux compensation. The achievement of this proposed control method is to maintain the standard performance of the motor drive at low speeds to reduce the power loss of the inverter unit compared to the conventional methods. In the proposed control method, the rotor flux is compensated with a PI controller. The proposed control scheme is based on the independent control of the rotor flux and the electromagnetic torque in the direct and orthogonal axises (d and q-axis), respectively. The rotor flux is compensated via reformed of the reference rotor flux. Also in this paper, for the first time, the reduction in number of switching elements of the inverter unit for the DSWIM drive can be achieved by utilizing five-leg and nine-switch power electronic converters. The advantages of using these proposed structures in the DSWIM drive are the reduction of the capital cost and also the reduction of power loss in the inverter unit.
http://joc.kntu.ac.ir/article-1-441-en.html
Dual stator winding
five-leg inverter
induction motor drive
nine-switch inverter
vector control.
per
Iranian Society of Instrumentation and Control Engineers
Journal of Control
2008-8345
2538-3752
2018-06
12
2
67
75
article
Maximum Power Point Tracking of a Photovoltaic System Using Modified Incremental Algorithm and Model Predictive Control
Ahmad Dehghanzadeh
a.dehghanzadeh.s@gmail.com
1
Gholamreza Farahani
farahani.gh@irost.ir
2
Mohsen Maboodi
maboodi.mohsen@mapnaec.com
3
Iranian Research Organization for Science and Technology
Iranian Research Organization for Science and Technology
Condition Monitoring Department, MAPNA Electrical and Control Engineering and Manufacturing Company (MECO), Mapna Blvd, 6th km Malard Road, Karaj, Iran
In this paper a systematic methodology to design a modified incremental conductance and a model predictive control (MPC) for maximum power point tracking of a photovoltaic system is presented. The PV system includes a PV module that supplies a DC link and also an energy storage system using a buck DC-DC converter. The incremental conductance (INC) method with two modifications is employed for maximum power point tracking (MPPT) within P-V characteristic curve according to changes in weather condition. To avoid a finite set control signal, the average model of the PV system is analytically calculated and subsequently the model is linearized around MPP. Designing an MPC with continuous control set, its performance respect to finite control set MPC is compared. The simulations demonstrate that the proposed controller with augmented integrator could track the MPP faster and with less steady state error.
http://joc.kntu.ac.ir/article-1-521-en.html
PV system
model predictive control (MPC)
finite control set MPC (FCS-MPC)
Incremental conductance.