Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : control

Thermal Performance of an Evacuated-Tube Solar Collector Using Nanofluids and an Electrical Curtain Controlled by an Artificial Intelligence Technique

Hussam J. Rashid; Khalid F. Sultan; Hosham S. Anead

Engineering and Technology Journal, 2022, Volume 40, Issue 1, Pages 8-19
DOI: 10.30684/etj.v40i1.2021

This paper studies the improvement of an evacuated tube solar collectors(ETSCs) performance in two way. The first is by adding a finned electronic curtain in front of the solar collector. While the second is by using a nanofluid instead of pure water. The purpose of the curtain is to increase the amount of solar radiation reflected toward the collector. The curtain is distinguished by its self-ability to track the sun's rays automatically. The electronic curtain is also closed to shade the tubes depending on the movement of the electronic curtain's fins and the nanofluid's temperatures. MATLAB algorithm has been used to design the Simulink model and control the system using Fuzzy Logic Control (FLC) and Artificial Neural Network (ANN). The results showed that the system performance improved using TiO2(50nm)+PW) as a working fluid without the curtain are (3.906%,5.34%, and7.407%), while the rate of improvement in the case of distilled water only was 2.34%and3.81%. Finally, by adding the finned electronic curtain to the system and use of TiO2(50nm)+PW) as a working fluid, the efficiency increased by 7.03%,9.16%, and 11.89%. The results showed that the performance of evacuated tubes solar collectors increased by using a nanofluid and the finned electronic curtain.

Modeling and Control of Wheeled Mobile Robot With Four Mecanum Wheels

Sameh F. Hasana; Hasan M. Alwan

Engineering and Technology Journal, 2021, Volume 39, Issue 5A, Pages 779-789
DOI: 10.30684/etj.v39i5A.1926

This work presents a driving control for the trajectory tracking of four mecanum wheeled mobile robot (FMWMR). The control consists of Backstepping-Type 1 Fuzzy Logic-Particle swarm optimization i.e.,(BSC-T1FLC-PSO). The kinematic and dynamic models have been derived. Backstepping controller (BSC) is used for finding controlled torques that generated from robot motors while Type-1 fuzzy logic control (T1FLC) as well as particle swarm optimization (PSO) used for finding the appropriate values of gain parameters of BSC. Square trajectory has been selected to test the performance of the control system of FMWMR. MATLAB/ Simulink is used to simulate the results. It has been concluded from the results that obtained from this control system there is a good matching between the simulated and the desired trajectories.

Assessing the performance of the evacuated tube solar collector using smart curtain through (PSO based PID) controller and Nano fluids

Hosham S.Anead; Khalid F. Sultan; Sura Abdul Jabbar

Engineering and Technology Journal, 2021, Volume 39, Issue 1A, Pages 137-152
DOI: 10.30684/etj.v39i1A.1701

This research revealed control on Nano fluid temperature in the evacuated tube solar collector system, where Nano fluids used in ETSC as working fluid to increase heating system thermal efficiency. Smart curtain was used to shadow the evacuated tube solar collector and to control the temperature of the Nano fluid in heating or cooling condition which is moved by the stepper motor which is programmed to move through the Arduino board using an artificial intelligence method such as (PSO based PID) controller method . Where the curtain's main idea is to control the polarization of the sun's radiation, the work of the curtain refers to the parameters: the first parameter is the Nano fluid temperature and the second is sun radiation falling on the collector, and one output parameter is defined by (distance parameter).

Optimal Quantitative Controller Design for Twin Rotor MIMO System

Mustafa K. Khreabet; Hazem I. Ali

Engineering and Technology Journal, 2020, Volume 38, Issue 12, Pages 1880-1894
DOI: 10.30684/etj.v38i12A.1618

In this paper, the control approach is used for achieving the desired performance and stability of the twin-rotor MIMO system. This system is considered one of the complex multiple inputs of multiple-output systems. The complexity because of the high nonlinearity, significant cross-coupling and parameter uncertainty makes the control of such systems is a very challenging task. The dynamic of the Twin Rotor MIMO System (TRMS) is the same as that in helicopters in many aspects. The Quantitative Feedback Theory (QFT) controller is added to the control to enhance the control algorithm and to satisfy a more desirable performance. QFT is one of the frequency domain techniques that is used to achieve a desirable robust control in presence of system parameters variation. Therefore, a combination between control and QFT is presented in this paper to give a new efficient control algorithm. On the other hand, to obtain the optimal values of the controller parameters, Particle Swarm Optimization (PSO) which is one of the powerful optimization methods is used. The results show that the proposed quantitative control can achieve more desirable performance in comparison to control especially in attenuating the cross-coupling and eliminating the steady-state error.