Mr. Karam Samir Khalid; Assist. Prof. Dr. Hazem I. Ali
Volume 14, Issue 3 , December 2014, Page 1-9
Abstract
Abstract – In this paper the design of robust Active Queue Management (AQM) for
congestion control in computer networks is presented. The Ant Colony Optimization
(ACO) method is used to tune the parameters of PID controller subject to H-infinity
constraints. The nonlinear dynamic model for multiple ...
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Abstract – In this paper the design of robust Active Queue Management (AQM) for
congestion control in computer networks is presented. The Ant Colony Optimization
(ACO) method is used to tune the parameters of PID controller subject to H-infinity
constraints. The nonlinear dynamic model for multiple TCP flows control is developed
based on fluid-flow theory. The designed controller provides good tracking performance
in the presence of wide range of system parameter uncertainty. NS2 package is used to
perform the nonlinear simulation of the system.
Hind Z. Khaleel; Dr. Firas A. Raheem
Volume 14, Issue 3 , December 2014, Page 10-20
Abstract
Abstract –Hexagonal hexapod robot is a flexible mechanical robot with six legs. It
has the ability to walk over terrain. The hexapod robot likes insect so it has the same
periodic gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to
stay statically stable at all the times ...
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Abstract –Hexagonal hexapod robot is a flexible mechanical robot with six legs. It
has the ability to walk over terrain. The hexapod robot likes insect so it has the same
periodic gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to
stay statically stable at all the times during each gait in order not to fall with three or
more legs continuously contacts with the ground. The safety static stability walking can
be indicated by the stability margin. In this paper we based on the forward, inverse
kinematics for each hexapod’s leg to simulate the hexapod robot model walking for all
periodic gaits and the geometry in order to derive the equations of the sub-constraint
workspaces for each hexapod’s leg. They are defined as the sub-constraint workspaces
volumes when the legs are moving without collision with each other and they are useful
to keep the legs stable from falling during each gait. A smooth gait was analyzed and
enhanced for each hexapod’s leg in two phases, stance phase and swing phase. The
equations of the stability margins are derived and computed for each gait. The
simulation results of our enhanced path planning of the hexapod robot approach whish’s
include all the gaits are statically stable and we are compared between all stability
margins for each gait. In addition, our results show clearly that the tripod gait is the
fastest gait while the wave and the ripple gaits are more stable than the tripod gait but
the last one has less peaks of stability margins than others.
Saad Jabbar Abbas; Alexander N. Grachev; Ali Hussein Hasan
Volume 14, Issue 3 , December 2014, Page 21-29
Abstract
Abstract –Accurate on-line estimates of critical system states and parameters are
needed in a variety of engineering applications, such as condition monitoring, fault
diagnosis, and process control. In these and many other applications it is required to
estimate a system variable which is not easily ...
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Abstract –Accurate on-line estimates of critical system states and parameters are
needed in a variety of engineering applications, such as condition monitoring, fault
diagnosis, and process control. In these and many other applications it is required to
estimate a system variable which is not easily accessible for measurement, using only
measured system inputs and outputs.
The classical identification methods, such as least-square method, are calculus-based
search method. They have many drawbacks such as requiring a good initial guess of the
parameter and gradient or higher-order derivatives of the objective function are
generally required also there is always a possibility to fall into a local minimum. In this
paper we develop on-line, robust, efficient, and global optimization identification for
parameters estimation based on genetic algorithms. The simulation results show that the
proposed algorithm is very fast to find and adapt the estimated parameters.
Abdulmohaimen B. Kassim; Asst. Prof. Dr. Shibly Ahmed Al-Samarraie; Prof. Dr. Waladin K. Sa
Volume 14, Issue 3 , December 2014, Page 30-41
Abstract
Abstract –In this paper, a mobile manipulator consisting of four degrees of freedom
(4-DOF) robotic manipulator mounted at the top of a mobile platform (front point) of a
mobile robot with four differential drive wheels is presented. A mobile manipulator
combines the dexterous manipulator capability ...
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Abstract –In this paper, a mobile manipulator consisting of four degrees of freedom
(4-DOF) robotic manipulator mounted at the top of a mobile platform (front point) of a
mobile robot with four differential drive wheels is presented. A mobile manipulator
combines the dexterous manipulator capability offered by fixed-based manipulators and
the mobility offered by the mobile robot. The work involves the modeling of mobile
manipulator robot and using the partial feedback linearization approach. The central
idea is to algebraically transform nonlinear systems dynamics into partially linear form,
so that linear control techniques can be applied to control on the wheel mobile
manipulator robot in order to track any trajectory such as an ellipse, circle….etc,
without violating the non holonomic constraints. However, and in order to consider the
uncertainty in system parameters and the effects of the external disturbances a nonlinear
PID controller is proposed in this work. The results demonstrate a good ability of the
designed nonlinear PID controller in regulating the mobile robot to track the desired
path in the presence of the external disturbances and the uncertainty in system
parameters
Dr. Amjad J. Humaid; Dr. Hamid M. Hasan; Dr. Firas A. Raheem
Volume 14, Issue 3 , December 2014, Page 42-51
Abstract
Abstract— Nowadays congestion in computer networks is pointed out as an
important and a challenging problem. TCP (Transmission Control Protocol) has the
mechanism to avoid congestion in computer networks. TCP detects congestion by
checking acknowledgements or time-out processing and adjusts TCP ...
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Abstract— Nowadays congestion in computer networks is pointed out as an
important and a challenging problem. TCP (Transmission Control Protocol) has the
mechanism to avoid congestion in computer networks. TCP detects congestion by
checking acknowledgements or time-out processing and adjusts TCP window sizes of
senders. However, this control method shows low efficiency in communications
because it is based on a mechanism that avoid congestion after congestion once appears
in computer networks. TCP random early detection RED is another popular congestion
control scheme. The fundamental idea behind this control algorithm randomly drops the
incoming packets proportional to the average queuing length and to keep the queuing
length to a minimum. To achieve high efficiency and high reliability of communications
in computer networks, many control strategies based on advanced control theories have
been introduced to tackle the congestion problem. Model Predictive Control (MPC) is
the only practical control method that takes account of system constraints explicitly, and
the only ‘advanced control’ method to have been adopted widely in industry. MPC is a
model-based method which uses online optimization in real time to determine control
signals. The solution to optimization problem is usually formulated with the help of a
process model and measurements. At each control interval, an optimization algorithm
attempts to determine the plant dynamics by computing a sequence of control input
values satisfying the control specifications. In this work, a planning strategy based on
MPC will be developed for congestion control problem. A "preset controllers" approach
will be introduced for such application. The effectiveness of considered controller will
assessed in terms of how well it could show good tracking performance, maximizing the
utilization of the available bandwidth and to what extent it could cope with system
uncertainties.
Dr. Mazin Z. Othman; Shaima B. Ayoob
Volume 14, Issue 3 , December 2014, Page 52-58
Abstract
Abstract – The Recursive Least Squares (RLS) is usually utilized in control
applications as in self-tuning strategy to estimate the plant discrete-time transfer
function. Furthermore, it can be used as a tool to continuously monitoring the operating
condition of the plant under control. However, ...
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Abstract – The Recursive Least Squares (RLS) is usually utilized in control
applications as in self-tuning strategy to estimate the plant discrete-time transfer
function. Furthermore, it can be used as a tool to continuously monitoring the operating
condition of the plant under control. However, in such applications, the RLS should be
always in a “wake up” state so that it can estimate, in a few sampling time, the plant
transfer function after any abrupt change in its dynamic.
In this work, two modifications to the standard RLS are presented. The first
modification is called the “switching forgetting factor” while the other is called the”
resetting covariance matrix”. The two modifications are applied, under LabVIEW
environment, on-line to estimate the proper transfer function of a DC motor as an
example to show their capabilities to monitor the motor operation. It is found that with
these modifications, the RLS can estimate the plant transfer function much faster in
comparison to the standard RLS algorithm.
Ahmed Ibraheem Abdulkareem
Volume 14, Issue 3 , December 2014, Page 59-70
Abstract
Abstract – This work introduces the implementation of particle system to be
simulated to work as a group of unmanned mobile robots (swarm robots). These robots
are able to locate a specified target in the predefined environment with high efficiency
when driven by an optimized Particle Swarm Optimization ...
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Abstract – This work introduces the implementation of particle system to be
simulated to work as a group of unmanned mobile robots (swarm robots). These robots
are able to locate a specified target in the predefined environment with high efficiency
when driven by an optimized Particle Swarm Optimization (PSO) algorithm. The
application of the particle system to the mobile robots to search for a target in the
environment is called Collective Robotics Search (CRS) problem. The main benefit of
this application is to evolve better solutions than using single robot through the
collective interaction of all robots between them to achieve the searching task
successfully. Particle system has been chosen in this work to employ the mobile robots
in the CRS problem due to its simplicity and easy to implement. To measure the
performance of this simulation, a simple obstacle free environment will be used to
implement behaviors of the group of mobile robots when those robots are used to search
for a single target. The results of this work show that applying PSO to a CRS problem
in off-line and on-line approaches are efficient in terms of minimum error and also
minimum number of iterations during the evolutionary process.