Optimal PID controller for coupled-tank liquid-level control system using bat algorithm

Katal, Nitish; Kumar, Parvesh; Narayan, Shiv

doi:10.1109/icpces.2014.7062818

Cited by 18 publications

(8 citation statements)

References 2 publications

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“…The BA for optimizing PID parameters has been used in a variety of process plants with encouraging results. In Katal et al (2014), BA was utilized to fine-tune the PID controller parameters for a connected tank liquid level control system, which is widely used in the mineral oil, food manufacturing, and water purification companies. BA in Kotteeswaran and Sivakumar (2013) was used to fine-tune the settings of a centrally controlled PI controller for a coal gas turbine, which is a non-linear multidimensional process with complex relationships across control loops.…”

Section: Bat For Pid Tuningmentioning

confidence: 99%

Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

Bassi

Dada

Abidemi

et al. 2022

Heliyon

200

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Section: Bat For Pid Tuningmentioning

confidence: 99%

Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

Bassi

Dada

Abidemi

et al. 2022

Heliyon

200

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“…The HA-explorers adopt different heuristic algorithms as the tuner algorithm of PID and FPID controllers to optimize their coefficient. The optimization algorithms employed include the following: genetic algorithm (GA) [37,38], particle swarm optimization (PSO) [39], bat Algorithm (BA) [40], chicken swarm optimization (CSO) [41], and grey wolf optimization (GWO) [42]. The controllers of different coefficients acquired from different optimization mechanisms provide the leader with diverse group of samples.…”

Section: Ha-explorer and Ensemble Intelligence Policymentioning

confidence: 99%

Distributed deep reinforcement learning for optimal voltage control of PEMFC

2021

IET Renewable Power Gen

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Proton exchange membrane fuel cells (PEMFCs) are promising components in the renewable energy field due to their high energy efficiency and low pollution output. However, these cells are also characterized by considerable nonlinearity, which in turn adversely affects the PEMFC output voltage. Conventional control algorithms cannot guarantee sufficient output voltage control, as they lack the robust adaptive ability required for adapting to these fluctuations in PEMFCs. In this paper, an optimal output voltage controller based on distributed deep reinforcement learning, which controls the output voltage by regulating the fuel input of the PEMFC, is proposed. In addition, an ensemble intelligence exploration multi-delay deep deterministic policy gradient (EIM-DDPG) algorithm is proposed for this controller. An ensemble intelligence exploration policy plus a classification experience replay mechanism are included within the EIM-DDPG algorithm to improve the exploration ability of the algorithm and thus increase the robustness and adaptive capability of the controller. As a result, the model-free optimal output voltage controller offers high robustness and adaptability. The simulation results in this paper demonstrate that the proposed optimal controller can realize the effective control of PEMFC output voltage.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…These bats will then work together towards the objective function (error minimization). In the proposed work it will work towards optimizing the controller parameters (Kp, Ki, Kd, N) based on ( 7)-( 9) [31][32].…”

Section: Pid Controller Design Using Bat Algorithmmentioning

confidence: 99%

Modeling and simulation of SEPIC controlled converter using PID controller

Khather¹,

İbrahim²

2020

IJPEDS

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<p>The topology of SEPIC "Single-ended primary inductance converter" is considered as a suitable option for automotive power system where the value of the output voltage should be ranging between the low and high values of the input value of voltage. The main feature of the DC-DC converter is the stability of output voltage. This paper shows the SEPIC converter employing PID converter to be used in industrial applications. A SEPIC DC-DC converter can manage either step-down mode or step-up mode. The benefit of using this circuit is to supply a stable and controlled output voltage no matter how much the input voltage is. The simulated behaviors of the uncontrolled and controlled SEPIC converter are presented in this paper. The PID controller based on bat algorithm (BA) optimization method is used for searching of the best Proportional–Integral-Derivative (PID) gains. The solution has given very good performance and whatever the output reference voltage variation and load disturbance of the system.</p>

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Optimal PID controller for coupled-tank liquid-level control system using bat algorithm

Cited by 18 publications

References 2 publications

Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

Distributed deep reinforcement learning for optimal voltage control of PEMFC

Modeling and simulation of SEPIC controlled converter using PID controller

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