Control
Wafeeq Sh. Hanna; Velar H. Elias; Dlawar R. Maruf
Abstract
The load forecasting is a human or computational technique foraccurate preanticipation of electrical load to enhance reliable operation andoptimal planning control of system plant for electrical energy flowing withoutfacing any economical and technical limitations, therefore appropriateestimation for ...
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The load forecasting is a human or computational technique foraccurate preanticipation of electrical load to enhance reliable operation andoptimal planning control of system plant for electrical energy flowing withoutfacing any economical and technical limitations, therefore appropriateestimation for present and future consumption cost of electrical loads which arenecessary to predict the load demand for generating near to accurate power.During advanced technology at the last few decades, artificial neuralnetworks(ANNs) have been extensively employed in electrical system, they aretrained using historical data obtained from plant station. This work is intendedto be a study of short-term load forecasting (STLF) basis for a power predictedapplied to the actual past load data displayed from Azadi station for Feb.2022were used in training and validation system of neural grid. The result wasevaluated by mean square percentage error of (32.7) for the forecastingdynamic time series method to solve the data over hours, days, and weeks inadvance, using a kind of non-linear filtering. Short-term load forecasting triedout with main stages; predicted power load data sets, network training, andforecasting. Neural network used has 3-layers: an input, a hidden, and anoutput layer. The number of hidden layer neurons can be varied for the differentnetwork performance. The active power generation faces economical andtechnical challenges, therefore appropriate evaluation of loads are muchneeded
Control
Ayad Q. Abdulkareem; Abdulrahim Th. Humod; Oday A. Ahmed
Abstract
To perform fault tolerance for Anti-lock Braking System (ABS), This paper proposes a hybrid Fault Detection and Fault Tolerant Control (FD-FTC) for ABS speed sensors. It utilizes a Fault Detection (FD) unit and a Data Construction (DC) unit. The first one, the FD unit, is based on a kNN classifier model ...
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To perform fault tolerance for Anti-lock Braking System (ABS), This paper proposes a hybrid Fault Detection and Fault Tolerant Control (FD-FTC) for ABS speed sensors. It utilizes a Fault Detection (FD) unit and a Data Construction (DC) unit. The first one, the FD unit, is based on a kNN classifier model with 99.9% fault detection accuracy to perform three tasks: early fault detection, fault location diagnosis, and excluding faulty signals from being utilized in further processes. On the other hand, the second one, the DC Unit, is based on two separate neural network models. These models have an MSE of 2.01139e-1 and a R2 of 999880 for the first model and an MSE of 1.12486e-0 and 0.999586 for the second model. They are employed to provide an estimated alternative signal for the ABS speed sensors. These estimated signals are employed to perform two tasks: confirming fault detection declared by the FD model and compensating for the excluded faulty signal to fulfill fault accommodation. Both methods are trained and tested with MATLAB and Simulink. Results demonstrate that the proposed hybrid method has the ability to accurately detect and tolerate sensor faults and fulfill its design purpose, especially during emergency braking.
Control
Aws M Abdullah; Farah F. Alkhalid; Ali Mohsin Kaittan
Abstract
The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Underthat paper, we think the fuzzy controller plan issue for yield following ...
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The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Underthat paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the field.In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use less hardware resources and operate with reasonable speed compared to other existing designs. The digital implementation of Fuzzy Logic Controller has been tested for a simulated first order liquid level process and the performance results have been compared with those of the Matlab version of Fuzzy Logic Controller. Here, Fuzzy Logic Controller is used as the controller and is trained adaptively for the changes in process parameters using recursive k-means clustering algorithm for updating the centers of the hidden layer and Recursive Least Square algorithm for updating the weights of the output layer, the result of the settling time about 20ms and takes 20 iterations, and the squared error reaches zero at approximately 20 µs
Control
Imad Zuhair; Hasan M Alwan; Hussain M. Al-Khafaji
Abstract
The expert system and artificial intelligence are still important modern technologies. A structure can modify its behavior under dynamic stresses by using active controls. The term "intelligent" or "smart" structures refers to these self-modifying structures. The structural engineering discipline may ...
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The expert system and artificial intelligence are still important modern technologies. A structure can modify its behavior under dynamic stresses by using active controls. The term "intelligent" or "smart" structures refers to these self-modifying structures. The structural engineering discipline may experience a revolution thanks to smart structure technologies. Particularly for huge structures, It is anticipated to have major effects. Effects with regard to the avoidance of fatalities and damage to the structure and its contents, particularly with regard to huge buildings that have thousands of elements. An efficient control algorithm to establish the magnitude of the actual forces to be applied to the construction is one of the most critical components in the successful use of smart active control technology. An overview of the primary active control approaches for the reduction of vibration in intelligent mechanical and civil structures that are subject to external dynamic loads is provided in this study. Different control algorithms' benefits and drawbacks are examined. Finally, recent advances in the study of control algorithms are highlighted, including the use of multiparadigm strategies, decentralized control, deep learning techniques applied to neural networks design of controls for sustainability, and a merging of the domains of vibration control and structural health monitoring.
Control
Ruaa S. Hassan; Farazdaq R. Yaseen
Abstract
Permanent Magnet Synchronous Motors (PMSM) are extensively used in the industry owing to their excellent efficiency, low weight/power ratio, and smooth torque with no or minimal ripple. Field Oriented Control (FOC) is a modern and effective approach for closed-loop controlling the speed of PMSM. In this ...
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Permanent Magnet Synchronous Motors (PMSM) are extensively used in the industry owing to their excellent efficiency, low weight/power ratio, and smooth torque with no or minimal ripple. Field Oriented Control (FOC) is a modern and effective approach for closed-loop controlling the speed of PMSM. In this paper, three-level Space Vector Pulse Width Modulation (SVPWM) is proposed for minimizing harmonics in the output voltage inverter. sensorless approaches are performed by using Model Reference Adaptive System (MRAS) which eliminates mechanical uncertainties. Because mechanical sensors increase the cost, size, weight, and wiring complexity, employing PMSM with them is extremely difficult Tuning of Proportional Integral (PI) controller gains is performed by using the Whale Optimization Algorithm (WOA). The results show that the proposed controller enhances the system's performance. In the application of felid-oriented control to a PMSM, with simulation data to back it up the entire system is simulated using the MATLAB/Simulink tool.
Control
Bashar F. Midhat
Abstract
In most applications, electric drives are actuated using on/off devices due to their low cost and also due to the relatively high power consumption of the electric drives which make applying linear power amplifiers very costly. In this paper, the operation of PMDC motors under discontinuous control action ...
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In most applications, electric drives are actuated using on/off devices due to their low cost and also due to the relatively high power consumption of the electric drives which make applying linear power amplifiers very costly. In this paper, the operation of PMDC motors under discontinuous control action is analyzed. In addition, to reduce chattering, boundary layer solution has been addressed. Both suggested control techniques have been applied to a PMDC motor model in a software simulation using MATLAB. The results show better performance of boundary layer technique due to the reduced chattering.
Control
Zahraa Ali Waheed; Amjad Jaleel Humaidi
Abstract
Physiotherapeutic exoskeleton devices have recently been developed to helppeople rehabilitate impaired limb mobility and replace the use of physiotherapists. Suchsystems are characterized by high nonlinear and time-varying coefficients. In order tocope with such difficult control challenges, a need arose ...
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Physiotherapeutic exoskeleton devices have recently been developed to helppeople rehabilitate impaired limb mobility and replace the use of physiotherapists. Suchsystems are characterized by high nonlinear and time-varying coefficients. In order tocope with such difficult control challenges, a need arose for reliable nonlinearcontrollers. While in this study the Sliding Mode Control (SMC) was used to track thetrajectory of the knee exoskeleton-system (KES) while having parameter uncertainty. Inaddition, the whale optimization algorithm (WOA) was introduced and developed toadjust the thickness design parameters for further optimization of its performance. Thesimulation was performed on a calculator using the MATLAB-Simulink program toconduct a comparative study between the optimal and Classical SMC where the resultsof comparison with the test parameters used by the SMC showed, the results of theproposed optimal SMC revealed that the positioning inaccuracy of the knee increased by31.8807% and it follows from this result that the controller could successfully performtracking the track well. Also, the control system created at the optimal thickness has abetter dynamic performance than the classical thickness.
Control
Nasir Ahmed Alawad; Amjad J Humaidi; Ahmed Sabah Alarejee
Abstract
Exoskeleton robots help users with mechanical forces by recognizing their intentions, and they require a lot of energy efficiency, a lot of load capacity, and a good fit. A basic one degree of freedom (DOF) construction was devised in this work, which was mostly used in the knees of exoskeleton robots. ...
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Exoskeleton robots help users with mechanical forces by recognizing their intentions, and they require a lot of energy efficiency, a lot of load capacity, and a good fit. A basic one degree of freedom (DOF) construction was devised in this work, which was mostly used in the knees of exoskeleton robots. The exoskeleton is a small robotic device used for knee injury training. It is a nonlinear mathematical model with many mechanical factors that might vary and produce uncertainty, as well as external disturbances that can be utilized to monitor control. The transitioning process is frequently organized using tracking differentiator TD to resolve the conflict between system speed and overshoot. An active disturbance rejection control (ADRC) with a modified tracking differentiator is described to tackle these challenges, enhance control accuracy, and reduce settling time for exoskeleton modified trajectory differentiator (MTD).Simulation tests showed that (MTD) reduced the tracking error by 36%, when compared with the improved TD1 and 37.5% for Hans TD2 at uncertainty case . Despite the presence of several model uncertainties, the suggested training knee exoskeleton robot system using the MTD-ADRC was able to achieve the necessary target value. Control design and analysis can be done with Matlab and Simulink
Control
Mayyasah Ali Salman; Saleem Khalefa Kadhim
Abstract
The lower limb amputees are increasing day by day. This has led to an increase in research in the field of prosthetic knee. In this work, a prosthetic knee was designed and developed to assist human movements and more quality of life for millions of individuals who have lost lower limbs. The dynamic ...
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The lower limb amputees are increasing day by day. This has led to an increase in research in the field of prosthetic knee. In this work, a prosthetic knee was designed and developed to assist human movements and more quality of life for millions of individuals who have lost lower limbs. The dynamic model and parameter identification of a two degree of freedom (2-DOF) joint prosthetic knee is derived according to the Lagrangian dynamic approach. The two controllers Backstepping and Adaptive Backstepping are adopted to control the system. Stability analysis and controller design dependent on Lyapunov theory are assessed to prove a tracking of a desired trajectory. From the results, found that the quantitative comparison between the two controllers, showed significant improvement in results in position tracking. To comparison between Backstepping control and Adaptive Backstepping control, at the control action consumptions. It was found that the position error of the prosthetic knee in Backstepping control is by 9% at link 1 (thigh) and 7.4% at link 2 (shank) compared with desired trajectory, while in Adaptive Backstepping control is by 1.16% at link 1 and 1.65% at link 2 compared with desired trajectory. When comparing between Backstepping control and Adaptive Backstepping control, the improvement rate was 7.84 at link 1 and 5.75 at link 2 , the proposed Adaptive Backstepping control, it may be concluded, is more robust against this perturbation and to deal with uncertainty. Therefore, the controller is built in a MATLAB environment, and its performance and robustness are assessed.
Control
Bashar F. Midhat
Abstract
Temperature control system is a widely applied process since temperature plays a major role in our life starting from room temperature conditioning to various industrial and medical applications. In this paper, a control algorithm is proposed for controlling the temperature of a certain process. Analysis ...
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Temperature control system is a widely applied process since temperature plays a major role in our life starting from room temperature conditioning to various industrial and medical applications. In this paper, a control algorithm is proposed for controlling the temperature of a certain process. Analysis is performed to verify the feasibility of the proposed control algorithm. A simulation is performed using MATLAB software to show the performance of the proposed control algorithm and a practical implementation is performed using Arduino to investigate the validity of the analysis. The results show the ability of the proposed controller to achieve the desired results which confirms the validity of the proposed controller and mathematical analysis.
Control
Ali M. Majeed; Safanah M. Raafat; Najat M. Ramadhan
Abstract
Wireless Sensor Network (WSN) represents a key network in the present and future Internet of Things (IoT) technology. WSN has an uncountable number of applications and is commonly used to aggregate information and control the physical environment remotely through small embedded devices known as wireless ...
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Wireless Sensor Network (WSN) represents a key network in the present and future Internet of Things (IoT) technology. WSN has an uncountable number of applications and is commonly used to aggregate information and control the physical environment remotely through small embedded devices known as wireless sensor nodes. Power consumption is one of the main challenges in WSN due to the limitation of power resources. Consequently, several techniques have been followed to optimize power consumption. The feedback control system is one of the routes that has been utilized to minimize power consumption in WSN using the mathematical model of power and rate control in WSN. In this paper, a concise review of various types of control systems that are deployed for power saving in WSN will be discussed. The comparison between the applied control strategies is the key finding.
Control
Hadeel I. Abdulameer; Mohamed J. Mohamed
Abstract
Four Fractional/Integer Order Fuzzy Proportional Integral Derivative controller structures are designed in this study to successfully control a nonlinear, coupled, multi-input, multi-output, three-link rigid robotic manipulator system. The performance of Fractional Order Fuzzy Proportional Integral Derivative ...
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Four Fractional/Integer Order Fuzzy Proportional Integral Derivative controller structures are designed in this study to successfully control a nonlinear, coupled, multi-input, multi-output, three-link rigid robotic manipulator system. The performance of Fractional Order Fuzzy Proportional Integral Derivative and Integer Order Fuzzy Proportional Integral Derivative controllers is evaluated for reference trajectory tracking, changing beginning circumstances, disturbance rejection, and model uncertainty. These controllers' parameters are tuned using a meta-heuristic optimization approach called the most valuable player algorithm for the objective function, which is defined as the integral of the time-squared error. Simulation results show that the suggested Fractional Order Fuzzy Proportional Integral Derivative controllers outperform Integer Order Fuzzy Proportional Integral Derivative controllers for tracking performance, stability, and robustness for all structures. Fractional Order Fuzzy Proportional Derivative Fractional Order Proportional Integral Derivative controller is the best one for trajectory tracking, disturbances rejection, and parameter variation with the least integral of time square error equal to 2.7420×10-6, 3.4×10-3 and 2.0108×10-4 respectively and the response of the angular position for all links for trajectory tracking has minimum settling time which is equal to 0.0290 s for the first link, 0.0160 s for the second link and 0.0050 s for the third link. When the initial condition is changed, the One Block Fractional Order Fuzzy Proportional Integral Derivative controller is the best one, since the integral of time square error is minimum and equal to 1.6253×10-4.
Control
Mustafa Laith Muhammed; Amjad Jaleel Humaidi; Enass Hassan Flaieh
Abstract
The search algorithms are characterized by their ability to find the optimal path in a short calculation time. In this study, a comparative analysis has been conducted to perform path planning of planar manipulator for static obstacle avoidance based on graph search algorithms. Four methods have been ...
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The search algorithms are characterized by their ability to find the optimal path in a short calculation time. In this study, a comparative analysis has been conducted to perform path planning of planar manipulator for static obstacle avoidance based on graph search algorithms. Four methods have been taken into account to establish a comparison platform; namely, conventional A*, modified A*, Chaos A*, and circulation heuristic search (CHS) algorithms. The performance of comparison is evaluated in terms of length of optimal path and consumption time of calculation. All algorithms have been coded and simulated within the MATLAB software environment. According to computer simulation, the results showed that CHS algorithms outperform the other graph search ones in terms of generated path length, while the Choas A* could give the least calculation time as compared to its counterparts.
Control
Ayat Naji Hussain; Sahar Adil Abboud; Basim Abdul baki Jumaa; Mohammed Najm Abdullah
Abstract
Human gait data follows distinct and identifiable patterns that are critical for movement analysis and evaluation Like other biological signals. The success of a rehabilitation program is dependent on the execution of proper progress monitoring. To ensure success, diagnosis of gait anomalies, as well ...
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Human gait data follows distinct and identifiable patterns that are critical for movement analysis and evaluation Like other biological signals. The success of a rehabilitation program is dependent on the execution of proper progress monitoring. To ensure success, diagnosis of gait anomalies, as well as the implementation of therapy to address them, must be validated in a constant and timely manner in developing youngsters. In this paper, machine learning techniques were utilized to classify foot diseases and the purpose is to increase the accuracy of disease detection and diagnosis because intelligent systems can contribute significantly in the medical field and have proven their worth in diagnosing many diseases. The results show high accuracy of the used machine learning algorithms, where the accuracy of the classifiers reached 100% for Random Forest (RF), Decision Tree (DT), and k-nearest neighbors (KNN), while it reached 98% for Logistic Regression.
Control
Ruaa Hameed Ahmed; Montadher Sami Shaker
Abstract
The paper presents an observer-based estimation of sensor fault for control systems affected by friction force. In such systems, the non-linearity of friction force leads to deteriorating sensor fault estimation capability of the observer. Hence, the challenge is to design an observer capable of attaining ...
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The paper presents an observer-based estimation of sensor fault for control systems affected by friction force. In such systems, the non-linearity of friction force leads to deteriorating sensor fault estimation capability of the observer. Hence, the challenge is to design an observer capable of attaining robust sensor fault estimation while avoiding the effects of friction. To overcome the highlighted challenge, an Unknown Input Observer (UIO) is designed to decouple the effects of friction as well as to estimate the state and sensor fault.The benefit of proposing UIO is to guarantee robust sensor fault estimation despite the highly non-linear disturbance in the form of friction. The gains of the UIO are computed through a single–step linear matrix inequality. Finally, an inverted pendulum simulation is presented to demonstrate the novel approach's performance effectiveness.
Index Terms—Robust fault estimation; Fault-Tolerant control; unknown input observer; Friction force; estimation/decoupling approach. Index Terms—Robust fault estimation; Fault-Tolerant control; unknown input observer; Friction force; estimation/decoupling approach.
Control
Fatimah I. Hussein; Safanah Raafat
Abstract
The control technique for an exoskeleton system for lower limb rehabilitation is complicated, and numerous internal and external elements must be taken into account, in addition to the uncertainties in the system model. In this paper, through the analysis of the lower extremity exoskeleton is utilized ...
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The control technique for an exoskeleton system for lower limb rehabilitation is complicated, and numerous internal and external elements must be taken into account, in addition to the uncertainties in the system model. In this paper, through the analysis of the lower extremity exoskeleton is utilized to obtain the corresponding equation and its linearized form. The nonlinear differential equations have been linearized by using Jacobean’s method in order to facilitate the controller design. Considering the interior and external factors of the connecting rod, the uncertain elements are introduced and therefore the optimal control technique is applied to regulate the system. An optimal state feedback control strategy of Linear Quadratic Regulator (LQR), and LQR-Servo have been implemented in this work. Finally, the physical parameters of the Knee-Ankle Orthosis (KAO) exoskeleton are used, and the simulation results show the advantage and applicability of the proposed controller’s design of the Knee-Ankle orthosis system.
