Dual stage cascade controller for temperature control in greenhouse

Abood, Layla H.; Kadhim, Nahida Naji; Mohammed, Yousra Abd

doi:10.11591/eei.v12i1.4328

Cited by 7 publications

(3 citation statements)

References 22 publications

(30 reference statements)

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“…The simulation analysis of the AVR system based on various optimal controllers is discussed in this section; the three controllers are studied and investigated to obtain a stable and robust system response based on SFO algorithm, Table 2 below lists the SFO algorithm parameter and the AVR system block diagram is indicated in Figure 4. For efficient monitoring and tracking to the desired response and to achieve best controlling to the terminal voltage value, an Integral Time Absolute Error (ITAE) function [19] is adopted as a fitness function, it is represented by a mathematical formula that depends on error value calculated between desired and actual values wanted and the instanteous time when running the algorithm to find the optimal prameters, its variables are the error and the time as indicated in Eq. ( 19), it is adopted as a cost function [20,21] to test the error when the SFO is run until reach to the most suitable gains values and that make the sysetm give a stable wanted behavior, as indicated in Figure 5 below.…”

Section: Simulation Resultsmentioning

confidence: 99%

Performance Evolution of Different Optimal Controllers for Controlling AVR System

Mohamed,

Abood

2023

JESA

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The main issue in electrical system is providing a stable voltage values in order to obtain best devices performance for this reason controlling the automatic voltage regulation (AVR) system becoma more helpful to achieve this requirments, in this paper three controllers are suggested for maintaining the terminal voltage level value of the generator part in AVR system that supplied to custumers, these controllers are (Conventional PID, ArcTan PID and Nonlinear PID), all gains of these controllers is tuned by using an intelligent sun flower optimization (SFO) algorithm. The objective of the design is finding suitable values of these gains that give a stable response based on minimizing error value and testing it using the Integral Time Absolute Error (ITAE) fitness function, the numerical results exhibited that the ArcTan PID controller give the best results values with a lower settling time (0.698) and its faster than conventional PID 5.034 % and faster than nonlinear PID by 5.163% for 5 second simulation time also its reach its peak value in 0.513 sec. and an expectable overshoot value equal to 0.513 with a small error value (0.000645) at its steady state case and then small error value when working at normal state without any disturbance or any uncertainty cases applied but when a disturbances signal is applied with a value equal to ± 0.3 to the system, the NLPID and the conventional PID presents a best response by returning the system to its desired value in just 2 second in the two cases applied and when change the gain values of two parts of AVR system( amplifier & sensor) the NLPID behaves as a the more suitable one and give a superior robust performance in facing this unwanted signals and then a desired response is achieved after small period time with satisfied and acceptable values for woring in this enviroment.

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Section: Simulation Resultsmentioning

confidence: 99%

Performance Evolution of Different Optimal Controllers for Controlling AVR System

Mohamed,

Abood

2023

JESA

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“…The proposed system utilizes a proportional integral and derivative (PID) controller as a temperature controller. PID controller has several proportional, integral, and derivative parameters, as seen in Figure 1 [28]- [32]. From Figure 1, 𝑅(𝑠) is the system input/setpoint, 𝐶(𝑠) is the system output, 𝐺(𝑠) is the system being controlled, that is the positive temperature coefficient (PTC) heater, and 𝐻(𝑠) is the system feedback, the AHT10 sensor.…”

Section: Methods 21 Control Systemmentioning

confidence: 99%

Controlling temperature using proportional integral and derivative control algorithm for hybrid forced convection solar dryer

Arifin,

Pangaribuan,

Pramudita

et al. 2024

IJECE

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Drying is one of the crucial processes in agricultural production, especially in grain processing. The drying process can improve grain quality and affect the grain content. However, maintaining the temperature is a challenge in the drying process. Because it can influence the drying performance and produce a low-efficiency reduction of water content, in this study, the hybrid drying system is proposed to improve the performance of the forced convection dryer system. The proposed system used a proportional integral and derivative (PID) control system to obtain the optimal temperature. The proposed system was compared with natural drying and forced convection methods. The experimental result showed that the proposed system performed excellently for three performance evaluations. The average temperature was obtained as the highest of the other methods, with 54.68 °C and 54.55 °C for coffee and cocoa beans. The water content can be reduced by an average of 27.38% and 42.67% for coffee and cocoa beans. Then, the proposed system also had the highest reduction efficiency of water content than the other methods, with 62.71% and 36.94% reductions for coffee and cocoa beans, respectively. The results indicate that the proposed hybrid system performs better than the other methods.

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“…PID controllers is regarded as a simple and classical controllers that adopted for improving system behavior. Nowadays, studies are made with a different changes for PID controller like combining it with a neural network [19,20] or changing its structure to reach to a best stability and robustness as in [21,22] or changing it by add a fractional variables (integral & derivative) to the classical PID to improve system output [23,24], this type of change is an augmented type PID controller. These parameters (μ for derivative variable and λ for the integral variable) make the gains of controller be five variables.…”

Section: Fopid Controllermentioning

confidence: 99%

Design an Optimal Fractional Order PID Controller for Speed Control of Electric Vehicle

Kadhim,

Abood,

Mohammed

2023

JESA

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In recent years, electric vehicles have garnered significant attention due to their environmental and economic advantages compared to conventional vehicles, including reduced emissions and lower fuel costs. This study proposes an optimal fractional-order PID (FOPID) controller to regulate electric vehicle (EV) speed. The FOPID controller is advantageous due to its ability for stabilizing the system, managing parameter variations, and mitigating potential disturbances. The tuning of this controller's gains is achieved through an intelligent Ant Colony Optimization (ACO) algorithm. The selection of the gain values is strategically based on minimizing error, thereby ensuring a robust system response without overshoot or undershoots. The performance of the proposed controller is analyzed and compared to a classical PID controller for demonstrating its superior performance. Simulation results illustrate the efficiency of the proposed controller, which exhibits no fluctuation or oscillation in its response (zero overshoot) and fast settling and rise times of 0.0476 and 0.0297, respectively. By using the optimal gains determined by the smart ACO, the proposed controller achieves a satisfactory and robust system response in controlling EV speed.

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Dual stage cascade controller for temperature control in greenhouse

Cited by 7 publications

References 22 publications

Performance Evolution of Different Optimal Controllers for Controlling AVR System

Performance Evolution of Different Optimal Controllers for Controlling AVR System

Controlling temperature using proportional integral and derivative control algorithm for hybrid forced convection solar dryer

Design an Optimal Fractional Order PID Controller for Speed Control of Electric Vehicle

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