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Go to Editorial ManagerThree-phase induction motors (IM) are widely utilized in various applications such as fans, milling machines, conveyor systems, robotics, pumps, and heavy machinery. Tasks that require precise speed control often demand additional control systems to ensure efficient and accurate operation. Unfortunately, the speed control of induction motors is a difficult problem due to system nonlinearity, parameter variations, and external disturbances. Therefore, standard proportional-integral-differential (PID) control systems are among the various techniques available for motor speed regulation. In this paper, the PID controller is used as a criteria to assess the efficacy of the proposed approach. This work specifically addresses the use of a toolbox controller for active disturbance rejection control (ADRC) to control the speed of a three-phase IM. The ADRC toolbox is a software tool (often a MATLAB/Simulink toolbox or library) designed to help users implement ADRC methods in their systems without having to code the algorithms from scratch. The speed performance of the motor was compared between PID and ADRC controllers. The evaluation was performed under steady state operation, with the intention of establishing and maintaining the speed of 1400 rpm. By simulation, the performance of the controllers in respect of rise time, settling time and the current consumption in all the simulations was analyzed conducted through MATLAB/Simulink. Simulation data indicate that the ADRC system outperforms conventional PID controllers when used with induction motors. Performance indicators such as ITAE (14.3 vs. 19.7), ISE (234.01 vs. 251.13), and RMSE (644.21 vs. 660.62) demonstrate that the ADRC system provides higher accuracy, faster response, and more efficient speed regulation control compared to the PID system. The results reveal that ADRC has better performance, especially in disturbance suppression. starting current, which contributes to extending the motor’s operational lifespan. Additionally, ADRC ensures smooth acceleration of rotor speed with a lower rise time of 0.3s as well as settling time of 0.36s, allowing the system to reach steady-state speed more efficiently. ADRC is more adaptive to nonlinear and unpredictable settings than PID since it actively compensates for total disturbances and estimates them.
The goal of this paper is to present a study of tuning the Proportional-Integral-Derivative (PID) controller for control the position of a DC motor by using the Particle Swarm Optimization (PSO) technique as well as the Ziegler & Nichols (ZN) technique. The conventional Ziegler & Nichols (ZN) method for tuning the PID controller gives a big overshoot and large settling time, so for this reason a modern control approach such as particle swarm optimization (PSO) is used to overcome this disadvantage. In this work, a third order system is considered to be the model of a DC motor. Four types of performance indices are used when using the particle swarm optimization technique. These indices are ISE, IAE, ITAE and ITSE. Also study the effect of each one of these performance indices by obtaining the percentage overshoot and settling time when a unit step input is applied to a DC motor. A comparison is made between the two methods for tuning the parameters of PID controller for control the position of a DC motor is considered. The first one is tuning the controller by using the Particle Swarm Optimization technique where the second is tuning by using the Ziegler & Nichols method. The proposed PID parameters adjustment by the Particle Swarm Optimization technique showed better results than the Ziegler & Nichols’ method. The obtained simulation results showed good validity of the proposed method. MATLAB programming and Simulink were adopted in this work.
This paper aims to investigate the effect of using different types of pipelines with the servo hydraulic system enhanced with PID controllers tuned by fuzzy logic. The mathematical models of several types of pipelines with different specifications (i.e. area variations in the pipe, disturbance source, etc.) are developed. The effect of the modified pipelines on the position control system at spool displacement is tested,since the servo hydraulic systems are difficult to control due to nonlinearity and complexity of their mathematical models. A PID controller tuned using fuzzy logic technique is used to improve the servo hydraulic system response.The results show that the mathematical models of the pipelines have a significant effect on the performance of the position control system at spool displacement according to the used pipeline type.Furthermore, a more desirable time response specifications and less steady state error are achieved after using the proposed controller.
This research is devoted to design and implement a Supervisory Control and Data Acquisition system (SCADA) for monitoring and controlling the corrosion of a carbon steel pipe buried in soil. A smart technique equipped with a microcontroller, a collection of sensors and a communication system was applied to monitor and control the operation of an ICCP process for a carbon steel pipe. The integration of the built hardware, LabVIEW graphical programming and PC interface produces an effective SCADA system for two types of control namely: a Proportional Integral Derivative (PID) that supports a closed loop, and a traditional open loop control. Through this work, under environmental temperature of 30°C, an evaluation and comparison were done for two types of controls tested at low soil moisture (48%) and high soil moisture (80 %) to study the value of current, anode voltage, pipe to soil potential (PSP) and consumed power. The results show an decrease of 59.1% in consumed power when the moisture changes from the low to high level. It was reached that the closed loop controller PID is the best solution in terms of efficiency, reliability, fast response and power consumption.
Continuous Positive Airway Pressure (CPAP) ventilation remains a mainstay treatment for different respiratory disorders. Good pressure stability and pressure reduction during exhalation are of major importance condition to ensure the clinical efficacy and comfort of CPAP therapy. Obstructive Sleep Apnea (OSA) and today coronavirus (COVID-19) are the main two diseases mitigated by the CPAP. This paper introduced a systematic review of the CPAP design in terms of the hardware design, Simulation-based CPAP system, control algorithm, and the measured performance. The accuracy is used as measurement of performance and calculated from the pressure value. The accuracy was compared to the predefined U.S. Food and Drug Administration (FDA)-based threshold value in which it considers this value as a reference. The results related to the modern CPAP devices introduced in this study to explain the accuracy of experimental CPAP. These were compared with a commercial CPAP devices. Also, it was revealed how the results coincide with the error ratio defined by the FDA as an evaluation measurement. The FDA error ratio determines the performance of the optimized CPAP device. This work is the first review that presented the knowledge about engineering design of the CPAP system, so it will be the first in the literature.
The oil industry has a direct impact on the economic feasibility of other sectors and is considered to be the most important energy source used to turn the wheels of other industries. Therefore, it was necessary to pay attention and continuously develop this industry, to find the best modern techniques for designing, pre-commissioning and controlling process, to improve efficiency, preserve energy and achieve the highest production of costly components with the highest purity of the product. This study aims to provide a literary analysis of the stages of development and progress of the dynamics and control of the petroleum industry, in particular the distillation column, because it is multivariable with high interaction between control cycles, nonlinear behaviour and large gains. Control processes have undergone many developments and modernizations to achieve the best results. Various control methods have been used, ranging from simple proportional-integral-derivative controller (PID) to advanced control strategies such as model predictive control (MPC), multivariate model predictive control (MMPC), fuzzy logic control (FLC), quadratic dynamic matrix control (QDMC), artificial neural network control (ANN) and other advanced control techniques. The authors concluded from the review that the advanced control strategies superior than the conventional methods.