2024-11-07T15:33:40+03:30
http://joc.kntu.ac.ir/browse.php?mag_id=33&slc_lang=fa&sid=1
33-360
2024-11-07
10.1002
Journal of Control
JoC
2008-8345
2538-3752
10.52547/joc
2016
10
2
Design of Model free Terminal Sliding Mode Control for discrete time nonlinear systems
Nahid
Ebrahimi Meymand
n.ebrahimimeymand@modares.ac.ir
Sajaad
Ozgoli
ozgoli@modares.ac.ir
A model free terminal sliding mode controller has been proposed. The proposed controller is data driven i.e. based only on input and output data (thus, model free). This method employs a recursive nonlinear sliding surface. This leads to higher tracking precision and to finite time convergence of the response. The method uses “Model Free Adaptive Controller” approach, combined with “Discrete time Sliding Mode Controller” method. Boundedness of tracking error is proved analytically. Theoretical analysis also shows the superiority of the proposed method over Model Free Linear Sliding Mode Controller. Analysis results are confirmed via simulation
Terminal Sliding Mode Control
Data Driven Control
Model Free Adaptive Control
Discrete time Sliding Mode Control.
2016
9
01
1
12
http://joc.kntu.ac.ir/article-1-360-en.pdf
33-348
2024-11-07
10.1002
Journal of Control
JoC
2008-8345
2538-3752
10.52547/joc
2016
10
2
A sliding mode control scheme for fractional stochastic systems with state delay
Khosro
Khandani
khosro.khandani@modares.ac.ir
Vahid
Johari Majd
majd@modares.ac.ir
Mahdieh
Tahmasebi
tahmasebi@modares.ac.ir
In this paper, a new approach is proposed for stability analysis of fractional stochastic systems. By extending the concept of infinitesimal generator using the fractional Ito formula, it becomes possible to apply it in fractional stochastic systems for stability analysis by Lyapunov functions. Thereafter, the presented stability criterion is utilized to develop the sliding mode control scheme for fractional stochastic systems with state delay. The proposed design method ensures that the state trajectories reach the sliding surface in finite time with probability one. Stability analysis of the system at sliding mode is executed using the given fractional infinitesimal generator and the stability conditions are given in the form of linear matrix inequalities. To illustrate the efficiency of the results, the application of the method is presented for the pitch control of a variable speed wind turbine.
fractional stochastic system
fractional infinitesimal generator
sliding mode control
linear matrix inequalities
pitch control of a wind turbine.
2016
9
01
13
22
http://joc.kntu.ac.ir/article-1-348-en.pdf
33-232
2024-11-07
10.1002
Journal of Control
JoC
2008-8345
2538-3752
10.52547/joc
2016
10
2
Adaptive Control of a Multi-Task Redundant Manipulator
Hamid
Sadeghian
h.sadeghian@eng.ui.ac.ir
Shahram
Hadian jazi
s.hadian@eng.ui.ac.ir
Mehdi
Keshmiri
mehdik@cc.iut.ac.ir
A nonlinear adaptive control algorithm for a multi-task redundant manipulator is developed in this paper. The method considers the parametric uncertainties in the system and defines a proper filtered error signal according to the allocated priority. Based on this error analysis, the asymptotic stability and convergence of the tracking error, both for the main task as well as the sub-tasks are shown using Lyapunov approach. In order to extend the algorithm for the case of orientation control in the operational task, quaternion feedback has been exploited, and the stability is shown. The results of the paper are verified in several simulations on 4DoF planar arm as well as 7DoF KUKA lightweight robot arm.
Multi-priority control
Nonlinear adaptive control
Null space
Quaternion feedback
2016
9
01
23
34
http://joc.kntu.ac.ir/article-1-232-en.pdf
33-291
2024-11-07
10.1002
Journal of Control
JoC
2008-8345
2538-3752
10.52547/joc
2016
10
2
An iterative algorithm for solving stochastic optimal control via the Markov chain approximation
Behzad
Kafash
Bkafash@ardakan.ac.ir
Zahra
Nikoeenezhad
Nikoueinezhad@yahoo.com
Ali
Delavarkhalafi
Delavarkh@yazd.ac.ir
In this paper, a numerical method for solving stochastic optimal control problem by using Markov chain approximation method has presented. The basic idea of the Markov chain approximation method is to approximate the original controlled process by an appropriate controlled Markov chain on a finite state space. Also, we need to approximate the original cost function by one which is appropriate for the approximating chain. These approximations should be chosen such that a good numerical approximation to the associated optimal control problem can be obtained, which means the conditional mean and covariance of the changes in state of the chain are proportional to the local mean drift and covariance for the original process. The finite difference approximations are used to the construction of locally consistent approximating Markov chain, the coefficients of the resulting discrete equation can serve as the desired transition probabilities and interpolation interval. The convergence is analogous to the convergence of a sequence of finite difference or finite element approximations to an original problem as the approximation interval goes to zero. Finally, we propose an iterative algorithm for solving stochastic optimal control and efficiency of the proposed algorithm is illustrated by an example.
solving stochastic optimal control problem
Markov chain approximation
Numerical method
iterative algorithm
2016
9
01
35
43
http://joc.kntu.ac.ir/article-1-291-en.pdf
33-347
2024-11-07
10.1002
Journal of Control
JoC
2008-8345
2538-3752
10.52547/joc
2016
10
2
Providing a new method for acoustic source DOA estimation based on TDoA by trigonometric methods
Ali
Naemi
alinaemi@chmail.ir
Hamid
Dehghani
hamid_deh@yahoo.com
Environmental surveillance and recognition are important issues to avoid surprises and conditions control. This awareness is necessary to combat and prevent the enemy attacks and increase deterrence. Direction of Arrival (DoA) estimation and localization targets are including the main bases environmental surveillance in an environment. DoA acoustic means calculated to enter acoustic wave emitted by the source in sensors that is provided different methods such as MVB, MUSIC and TDoA for this issue. The proposed method with simplification of trigonometric equations calculate the location is provided new equations to estimate direction of arrival acoustic signal for hemispherical environment that number equal to two-dimensional state. DoA estimation for hemisphere environment is provided for this reason, often with installed DoA estimation system on a platform is needed to be half of environment localization or DoA estimation and also just by adding a sensor, system will obtain the ability to work in sphere environment. In this simplification is decreases the computational complexity and the number of sensors needed to DoA estimation a hemisphere. In the proposed method is obtained the responses with acceptable error for elevation and azimuthal angles in simulations.
Direction of arrival estimation
Acoustic source
Time difference of arrival
Trigonometric method
Hemispherical environment
2016
9
01
45
54
http://joc.kntu.ac.ir/article-1-347-en.pdf
33-386
2024-11-07
10.1002
Journal of Control
JoC
2008-8345
2538-3752
10.52547/joc
2016
10
2
Adaptation of the Noise Covariance in Extended Kalman Filter Applied on Bearing Only Target Tracking Using Indirect Recursive Method
Meghdad
Mohammadi
meghdad.mohammadi@yahoo.com
Hossein
Gholizade-Narm
gholizade@shahroodut.ac.ir
This paper proposes a recursive method to determine the process and measurement noise covariance matrix in the extended Kalman filter in application of bearing-only target tracking. One of the requirements of Kalman filters is knowledge of process and measurement noise covariance matrices. If the inappropriate choice of covariance, the filter performance is affected and even there is the possibility of divergence. In this paper, a recursive structure to adapting noise covariance is presented that unlike the conventional methods, instead of direct adapting covariance matrices, based on steepest descent adapting rule structure parameters are adapted. This increases the reliability of the adaptive method and non-negative condition of some of covariance matrix elements to be resolved. To evaluate the performance of proposed method, the bearing-only target tracking scenario is considered. To compare the proposed approach, three adaptive covariance common methods is used that simulation results show that the reliability and efficiency of the proposed method.
State Estimation
Extended Kalman Filter
Covariance Adaptation
Bearing only Tracking
2016
9
01
55
72
http://joc.kntu.ac.ir/article-1-386-en.pdf