Abstract: Circular knitting machine makes the fabric with more than two knitting tools. Variation of yarn tension between different knitting tools causes different loop length of stitches duration knitting process. In this research, a new intelligent method is applied to control loop length of stitches in various tools based on ideal shape of stitches and real angle of stitches direction while different loop length of stitches causes stitches deformation and deviation those of angle. To measure deviation of stitch direction against variation of tensions, image processing technique was applied to pictures of different fabrics with constant front light. After that, the rate of deformation is translated to needed compensation of loop length cam degree to cure stitches deformation. A fuzzy control algorithm was applied to loop length modification in knitting tools. The presented method was experienced for different knitted fabrics of various structures and yarns. The results show that presented method is useable for control of loop length variation between different knitting tools based on stitch deformation for various knitted fabrics with different fabric structures, densities and yarn types.
Abstract: The effect of different combinations of response
feedback on the performance of active control system on nonlinear
frames has been studied in this paper. To this end different feedback
combinations including displacement, velocity, acceleration and full
response feedback have been utilized in controlling the response of
an eight story bilinear hysteretic frame which has been subjected to a
white noise excitation and controlled by eight actuators which could
fully control the frame. For active control of nonlinear frame
Newmark nonlinear instantaneous optimal control algorithm has been
used which a diagonal matrix has been selected for weighting
matrices in performance index. For optimal design of active control
system while the objective has been to reduce the maximum drift to
below the yielding level, Distributed Genetic Algorithm (DGA) has
been used to determine the proper set of weighting matrices. The
criteria to assess the effect of each combination of response feedback
have been the minimum required control force to reduce the
maximum drift to below the yielding drift. The results of numerical
simulation show that the performance of active control system is
dependent on the type of response feedback where the velocity
feedback is more effective in designing optimal control system in
comparison with displacement and acceleration feedback. Also using
full feedback of response in controller design leads to minimum
control force amongst other combinations. Also the distributed
genetic algorithm shows acceptable convergence speed in solving the
optimization problem of designing active control systems.
Abstract: A new topology of unified power quality conditioner
(UPQC) is proposed for different power quality (PQ) improvement in
a three-phase four-wire (3P-4W) distribution system. For neutral
current mitigation, a star-hexagon transformer is connected in shunt
near the load along with three-leg voltage source inverters (VSIs)
based UPQC. For the mitigation of source neutral current, the uses of
passive elements are advantageous over the active compensation due
to ruggedness and less complexity of control. In addition to this, by
connecting a star-hexagon transformer for neutral current mitigation
the over all rating of the UPQC is reduced. The performance of the
proposed topology of 3P-4W UPQC is evaluated for power-factor
correction, load balancing, neutral current mitigation and mitigation
of voltage and currents harmonics. A simple control algorithm based
on Unit Vector Template (UVT) technique is used as a control
strategy of UPQC for mitigation of different PQ problems. In this
control scheme, the current/voltage control is applied over the
fundamental supply currents/voltages instead of fast changing APFs
currents/voltages, thereby reducing the computational delay.
Moreover, no extra control is required for neutral source current
compensation; hence the numbers of current sensors are reduced. The
performance of the proposed topology of UPQC is analyzed through
simulations results using MATLAB software with its Simulink and
Power System Block set toolboxes.
Abstract: Due to the coexistence of different Radio Access
Technologies (RATs), Next Generation Wireless Networks (NGWN)
are predicted to be heterogeneous in nature. The coexistence of
different RATs requires a need for Common Radio Resource
Management (CRRM) to support the provision of Quality of Service
(QoS) and the efficient utilization of radio resources. RAT selection
algorithms are part of the CRRM algorithms. Simply, their role is to
verify if an incoming call will be suitable to fit into a heterogeneous
wireless network, and to decide which of the available RATs is most
suitable to fit the need of the incoming call and admit it.
Guaranteeing the requirements of QoS for all accepted calls and at
the same time being able to provide the most efficient utilization of
the available radio resources is the goal of RAT selection algorithm.
The normal call admission control algorithms are designed for
homogeneous wireless networks and they do not provide a solution
to fit a heterogeneous wireless network which represents the NGWN.
Therefore, there is a need to develop RAT selection algorithm for
heterogeneous wireless network. In this paper, we propose an
approach for RAT selection which includes receiving different
criteria, assessing and making decisions, then selecting the most
suitable RAT for incoming calls. A comprehensive survey of
different RAT selection algorithms for a heterogeneous wireless
network is studied.
Abstract: This paper introduces our first efforts of developing a
new team for RoboCup Middle Size Competition. In our robots we
have applied omni directional based mobile system with omnidirectional
vision system and fuzzy control algorithm to navigate
robots. The control architecture of MRL middle-size robots is a three
layered architecture, Planning, Sequencing, and Executing. It also
uses Blackboard system to achieve coordination among agents.
Moreover, the architecture should have minimum dependency on low
level structure and have a uniform protocol to interact with real
robot.
Abstract: Active vibration isolation systems are less commonly
used than passive systems due to their associated cost and power
requirements. In principle, semi-active isolation systems can deliver
the versatility, adaptability and higher performance of fully active
systems for a fraction of the power consumption. Various semi-active
control algorithms have been suggested in the past. This paper
studies the 4DOF model of semi-active suspension performance
controlled by on–off and continuous skyhook damping control
strategy. The frequency and transient responses of model are
evaluated in terms of body acceleration, roll angle and tire deflection
and are compared with that of a passive damper. The results show
that the semi-active system controlled by skyhook strategy always
provides better isolation than a conventional passively damped
system except at tire natural frequencies.
Abstract: In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the neural control of autonomous constant depth flight of an autonomous underwater vehicle (AUV). Autonomous constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth, and a properly designed controller to govern the process. The AUV, named VORAM, is used as a model for the verification of the proposed hybrid control algorithm. Three neural network controllers, named NARMA-L2 controllers, are designed for fast and stable diving maneuvers of chosen AUV model. This hybrid control strategy for chosen AUV model has been verified by simulation of diving maneuvers using software package Simulink and demonstrated good performance for fast SA in real-time searchand- rescue operations.
Abstract: Automated storage and retrieval systems (AS/RS)
become frequently used systems in warehouses. There has been a
transition from human based forklift applications to fast and safe
AS/RS applications in firm-s warehouse systems. In this study, basic
components and automation systems of the AS/RS are examined.
Proposed system's automation components and their tasks in the
system control algorithm were stated. According to this control
algorithm the control system structure was obtained.
Abstract: A considerable amount of energy is consumed during
transmission and reception of messages in a wireless mesh network
(WMN). Reducing per-node transmission power would greatly
increase the network lifetime via power conservation in addition to
increasing the network capacity via better spatial bandwidth reuse. In
this work, the problem of topology control in a hybrid WMN of
heterogeneous wireless devices with varying maximum transmission
ranges is considered. A localized distributed topology control
algorithm is presented which calculates the optimal transmission
power so that (1) network connectivity is maintained (2) node
transmission power is reduced to cover only the nearest neighbours
(3) networks lifetime is extended. Simulations and analysis of results
are carried out in the NS-2 environment to demonstrate the
correctness and effectiveness of the proposed algorithm.
Abstract: This paper presents a fuzzy control system for a three degree of freedom (3-DOF) stabilized platform with explicit decoupling scheme. The system under consideration is a system with strong interactions between three channels. By using the concept of decentralized control, a control structure is developed that is composed of three control loops, each of which is associated with a single-variable fuzzy controller and a decoupling unit. Takagi-Sugeno (TS) fuzzy control algorithm is used to implement the fuzzy controller. The decoupling units design is based on the adaptive theory reasoning. Simulation tests were established using Simulink of Matlab. The obtained results have demonstrated the feasibility and effectiveness of the proposed approach. Simulation results are represented in this paper.
Abstract: Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.
Abstract: This paper is concerned with the application of the vision control algorithm for robot's point placement task in discontinuous trajectory caused by obstacle. The presented vision control algorithm consists of four models, which are the robot kinematic model, vision system model, parameters estimation model, and robot joint angle estimation model.When the robot moves toward a target along discontinuous trajectory, several types of obstacles appear in two obstacle regions. Then, this study is to investigate how these changes will affect the presented vision control algorithm.Thus, the practicality of the vision control algorithm is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.
Abstract: Automotive engine air-ratio plays an important role of
emissions and fuel consumption reduction while maintains
satisfactory engine power among all of the engine control variables. In
order to effectively control the air-ratio, this paper presents a model
predictive fuzzy control algorithm based on online least-squares
support vector machines prediction model and fuzzy logic optimizer.
The proposed control algorithm was also implemented on a real car for
testing and the results are highly satisfactory. Experimental results
show that the proposed control algorithm can regulate the engine
air-ratio to the stoichiometric value, 1.0, under external disturbance
with less than 5% tolerance.
Abstract: This paper is aimed at describing a delay-based endto-
end (e2e) congestion control algorithm, called Very FAST TCP
(VFAST), which is an enhanced version of FAST TCP. The main
idea behind this enhancement is to smoothly estimate the Round-Trip
Time (RTT) based on a nonlinear filter, which eliminates throughput
and queue oscillation when RTT fluctuates. In this context, an evaluation
of the suggested scheme through simulation is introduced, by
comparing our VFAST prototype with FAST in terms of throughput,
queue behavior, fairness, stability, RTT and adaptivity to changes in
network. The achieved simulation results indicate that the suggested
protocol offer better performance than FAST TCP in terms of RTT
estimation and throughput.
Abstract: This paper presents an adaptive feedback linearization approach to derive helicopter. Ideal feedback linearization is defined for the cases when the system model is known. Adaptive feedback linearization is employed to get asymptotically exact cancellation for the inherent uncertainty in the knowledge of the given parameters of system. The control algorithm is implemented using the feedback linearization technique and adaptive method. The controller parameters are unknown where an adaptive control law aims to drive them towards their ideal values for providing perfect model matching between the reference model and the closed-loop plant model. The converged parameters of controller would then provide good estimates for the unknown plant parameters.
Abstract: The RK5GL3 method is a numerical method for solving
initial value problems in ordinary differential equations, and is
based on a combination of a fifth-order Runge-Kutta method and
3-point Gauss-Legendre quadrature. In this paper we describe an
effective local error control algorithm for RK5GL3, which uses local
extrapolation with an eighth-order Runge-Kutta method in tandem
with RK5GL3, and a Hermite interpolating polynomial for solution
estimation at the Gauss-Legendre quadrature nodes.
Abstract: According to investigating impact of complexity of
stereoscopic frame pairs on stereoscopic video coding and
transmission, a new rate control algorithm is presented. The proposed
rate control algorithm is performed on three levels: stereoscopic group
of pictures (SGOP) level, stereoscopic frame (SFrame) level and
frame level. A temporal-spatial frame complexity model is firstly
established, in the bits allocation stage, the frame complexity, position
significance and reference property between the left and right frames
are taken into account. Meanwhile, the target buffer is set according to
the frame complexity. Experimental results show that the proposed
method can efficiently control the bitrates, and it outperforms the fixed
quantization parameter method from the rate distortion perspective,
and average PSNR gain between rate-distortion curves (BDPSNR) is
0.21dB.
Abstract: In this paper we investigated a number of the Internet
congestion control algorithms that has been developed in the last few
years. It was obviously found that many of these algorithms were
designed to deal with the Internet traffic merely as a train of
consequent packets. Other few algorithms were specifically tailored
to handle the Internet congestion caused by running media traffic that
represents audiovisual content. This later set of algorithms is
considered to be aware of the nature of this media content. In this
context we briefly explained a number of congestion control
algorithms and hence categorized them into the two following
categories: i) Media congestion control algorithms. ii) Common
congestion control algorithms. We hereby recommend the usage of
the media congestion control algorithms for the reason of being
media content-aware rather than the other common type of
algorithms that blindly manipulates such traffic. We showed that the
spread of such media content-aware algorithms over Internet will
lead to better congestion control status in the coming years. This is
due to the observed emergence of the era of digital convergence
where the media traffic type will form the majority of the Internet
traffic.
Abstract: This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.