Metamodel-based Optimization of a PID Controller Parameters for a Coupled-tank System

Nafea, Marwan; Ali, A.; Baliah, Jeevananthan; Ali, Mohamed Sultan Mohamed

doi:10.12928/telkomnika.v16i4.9069

Cited by 15 publications

(9 citation statements)

References 15 publications

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“…The estimation of the five model parameters is carried out using PSO, a technique praised for its effectiveness in handling estimation and optimization related problems [27], [28]. This technique, developed by Eberhart and Kennedy, is developed from research on a form of swarm intelligence [29] using particles contained in an n-dimensional search space.…”

Section: B Model Formulationmentioning

confidence: 99%

PSO-Based SEIQRD Modeling and Forecasting of COVID-19 Spread in Italy

Abdallah

Nafea

2021

2021 IEEE 11th IEEE Symposium on Computer Applications &Amp; Industrial Electronics (ISCAIE)

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On 12 March 2020, Coronavirus disease (COVID-19) was declared as a pandemic by the World Health Organization. Efficient disease prevention is challenged by factors, such as population growth, insufficient documentation of clinical effects, dissemination mechanism, and lack of a reliable vaccine. Italy was heavily affected by COVID-19, causing it to have one of the highest COVID-19 deaths in the world. Current statistics show that Italy is on its own way to recover from the second wave of the virus. Therefore, this paper presents a susceptible-exposed-infected-quarantinedrecovered-dead (SEIQRD) model to model and predict the spread of the disease in Italy in the near future. The prediction is based on formulating the SEIQRD model using 365-day statistics of the disease. The parameters of the model are estimated using particle swarm optimization (PSO) algorithm. The modeling results agree well with the reported data, with normalized mean absolute error (NMAE) values ranging from 0.058 to 0.214 (average NMAE = 0.115), and normalized root mean absolute error (NRMSE) values ranging from 0.104 to 0.305 (average NRMSE = 0.190). The estimated PSO-based model is then used to predict the future of the disease in Italy in the coming 35 days. The forecasted results indicate that the number of infections will keep reducing, ending the second wave of COVID-19. Such results can assist governments around the world in the process of planning for countermeasures that help reduce the spread of the disease based on forecasted numbers.

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Section: B Model Formulationmentioning

confidence: 99%

PSO-Based SEIQRD Modeling and Forecasting of COVID-19 Spread in Italy

Abdallah

Nafea

2021

2021 IEEE 11th IEEE Symposium on Computer Applications &Amp; Industrial Electronics (ISCAIE)

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“…It is an easy-to-implement closed-loop controller method that enables to control the system using the proportional and integral sums of the PI error signal [18], [19]. Also, a basic PI Controller block diagram is given in Figure 4 in which Kp is the coefficient of proportional and Ki is the coefficient of integral.…”

Section: Proportional Integral (Pi) Controllermentioning

confidence: 99%

Power analysis of robotic medical drill with different control approaches

Torun

Malatyali

2020

Cumhuriyet Science Journal

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Increasing the efficiency of the systems used in surgical operations has become an important issue. Especially in orthopedic surgery, many surgical systems and instruments are used to reduce the workload of surgeons and increase the success of the operation. Surgical drills, which are one of these systems used in orthopedic surgery, are used in operations such as drilling, cutting and carving in various interventions. Cases such as drill sensitivity and stability are critical to operational success and patient health. In this study, an orthopedic drill design that can be added to a linear motion module or a 6-axis robot manipulator has been realized. Linear Quadratic Regulator (LQR), which is one of the optimal controller methods, Proportional Integral (PI) Controller, which is one of the classical controller methods and Model Predictive Controller (MPC) systems from modern controller systems are designed to perform speed control task of the surgical drill. A drill integrated into the robot manipulator for a constant drilling speed of 120 rad/sec and a robot manipulator were used to provide constant feed rate (1 mm/s) and to drill holes at constant intervals during the drilling experiments. Power analysis is performed in real-time in bone drilling operations for three controllers. Current, and voltage information during drilling are recorded simultaneously in the experimental setup. In particular, it has been observed that the power signal and the force information of the bone in different layers are proportional.

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“…Another common way of controlling the process systems with strong nonlinearities in the model-based predictive controller also known as MPC [7], [16]- [18]. There are many other strategies used for industrial process controller design such as artificial neural network (ANN) based controller [19], different optimization solutions as presented by [20], [21] using Pareto-based method, and radial basis function neural network metamodel respectively. Fuzzy predictive control [8] and internal model control (IMC), are discussed in [22].…”

Section: Introductionmentioning

confidence: 99%

“…While there are still some additions, it is acknowledged that after the first attempts done in the late eighties, significant progress in column flotation dynamic simulation has been made. According to the literature many good optimization techniques can be used for multi-objective systems [20], [21], but the cost associated with multivariable systems is still a major problem that prevents the general use of optimization techniques. Then again, many controller design methods are applied and published such as ANN, MPC, different optimization methods, and fuzzy logic control which seems to be the successful techniques [8], [19], [20], [23].…”

Section: Introductionmentioning

confidence: 99%

Decentralised PI controller design based on dynamic interaction decoupling in the closed-loop behaviour of a flotation process

Tshemese-Mvandaba

Tzoneva

Mnguni

2021

IJECE

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An enhanced method for design of decenralised proportional integral (PI) controllers to control various variables of flotation columns is proposed. These columns are multivariable processes characterised by multiple interacting manipulated and controlled variables. The control of more than one variable is not an easy problem to solve as a change in a specific manipulated variable affects more than one controlled variable. Paper proposes an improved method for design of decentralized PI controllers through the introduction of decoupling of the interconnected model of the process. Decoupling the system model has proven to be an effective strategy to reduce the influence of the interactions in the closed-loop control and consistently to keep the system stable. The mathematical derivations and the algorithm of the design procedure are described in detail. The behaviour and performance of the closed-loop systems without and with the application of the decoupling method was investigated and compared through simulations in MATLAB/Simulink. The results show that the decouplers - based closed-loop system has better performance than the closed-loop system without decouplers. The highest improvement (2 to 50 times) is in the steady-state error and 1.2 to 7 times in the settling and rising time. Controllers can easily be implemented.

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Metamodel-based Optimization of a PID Controller Parameters for a Coupled-tank System

Cited by 15 publications

References 15 publications

PSO-Based SEIQRD Modeling and Forecasting of COVID-19 Spread in Italy

PSO-Based SEIQRD Modeling and Forecasting of COVID-19 Spread in Italy

Power analysis of robotic medical drill with different control approaches

Decentralised PI controller design based on dynamic interaction decoupling in the closed-loop behaviour of a flotation process

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