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Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results show that the artificial neural network is the best method to control the CSTR process and it is better than the conventional method because it has smaller value of mean square error (MSE).   MATLAB program is used as a tool of solution for all cases used in the present work.

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Publication Date
Tue May 01 2018
Journal Name
2018 2nd Ieee Advanced Information Management,communicates,electronic And Automation Control Conference (imcec)
Hybrid Regressor and Approximation-Based Adaptive Control of Robotic Manipulators with Contact-Free Motion
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Publication Date
Wed Jan 14 2026
Journal Name
Journal Of Robotics And Control (jrc)
Intelligent Semi-Active Vibration Control of Automobiles: A Half-Car Model with Smart Dampers
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Semi-active suspension systems have emerged as an attractive alternative to fully active suspensions because they offer a superior capacity to improve vehicle ride comfort and handling performance with significantly lower energy consumption. Conventional semi-active control strategies, however, such as skyhook damping, often cannot accommodate the nonlinear and time-varying dynamics of vehicles in operation under impulse or severe road disturbances. In this context, an intelligent smart-damper controller is proposed in this paper by incorporating a Modified Fuzzy Adaptive Fuzzy Logic Control framework in a half-car suspension model. In the developed controller, the effective damping force is adaptively tuned using real-time measurements of

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Biological control of saw toothed beetle Oryzaephilus surinamensis(L.)Using fungi Lecanicillium lecanii(Zimm.)
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This study is conducted to determine the effect of pathogenicity of the fungus Lecanicillium lecanii in some aspects of life of the insect saw toothed beetle Oryzaephilus surinamensis L. (Coleoptera: Silvanidae) under laboratory conditions with three concentrations of spores and mildew commentator (1 × 103, 1 × 105, 1 × 107) spore / ml , on eggs and larvae second phase of the insect .The study also includs the effect of the fungus concentrations of germination on rice (jasmine) by using direct spray treatment. The results show great fungus efficiency in the control of some aspects of life of the insect, where varied efficiency depends on the concentration of spores, The highest percentage loss of eggs is 63.33% at a concentration

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Publication Date
Sun Jun 12 2022
Journal Name
Sensors
Recent Advances in Bipedal Walking Robots: Review of Gait, Drive, Sensors and Control Systems
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Currently, there is an intensive development of bipedal walking robots. The most known solutions are based on the use of the principles of human gait created in nature during evolution. Modernbipedal robots are also based on the locomotion manners of birds. This review presents the current state of the art of bipedal walking robots based on natural bipedal movements (human and bird) as well as on innovative synthetic solutions. Firstly, an overview of the scientific analysis of human gait is provided as a basis for the design of bipedal robots. The full human gait cycle that consists of two main phases is analysed and the attention is paid to the problem of balance and stability, especially in the single support phase when the biped

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Publication Date
Fri Jan 01 2021
Journal Name
Fme Transactions
FAT-based adaptive backstepping control of an electromechanical system with an unknown input coefficient
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This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Applied Biology & Biotechnology
Field treatment of three wheat varieties with Trichoderma harzianum bioagent to control Anguina tritici
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Publication Date
Mon Dec 01 2014
Journal Name
Advances In Engineering Software
System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm
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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
Design, Construction, and Control Tracking of Solar Thermal Concentrator by Using PLC in Erbil
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This paper demonstrates the construction designing analysis and control strategies for fully tracking concentrated solar thermal by using programmable logic control in the city of Erbil-Iraq. This work used the parabolic dish as a concentrated solar thermal. At the focal point, the collected form of energy is used for heating a (water) in the receiver, analyzing this prototype in real-time with two different shapes of the receiver and comparing the results. For tracking the parabolic dish, four light-dependent resistors are used to detect the sun's position in the sky so that the tracking system follows it to make the beam radiation perpendicular to the collector surface all of the time during the day for maximum solar p

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Publication Date
Tue May 13 2025
Journal Name
Journal Of Robotics And Control (jrc)
Bipedal Robots: A Systematic Review of Dynamical Models, Balance Control Strategies, and Locomotion Methods
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Bipedal robots, designed to replicate human locomotion, face significant balance challenges due to instability and high degrees of freedom. This study examines dynamical models, balance control strategies, and locomotion methodologies. Dynamical models are categorized into simplified, centroidal dynamics, and whole-body dynamics models. Simplified models, such as the Linear Inverted Pendulum Model (LIPM), approximate the robot as a point mass at the Center of Mass (CoM) but neglect upper-body dynamics and complex terrain interactions. Centroidal dynamics models incorporate CoM motion, contact forces, and angular momentum for improved disturbance rejection but require extensive computational resources. Whole-body models achieve high

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Scopus (11)
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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