A novel optimal PIλDND2N2 controller using coyote optimization algorithm for an AVR system

Moschos, Ioannis; Parisses, Constantinos

doi:10.1016/j.jestch.2021.04.010

Cited by 30 publications

(21 citation statements)

References 40 publications

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“…As is the case for the DC motor, a controller is also required for efficient operation of an AVR system. In that respect, several controller structures such as PID controller (Bingul and Karahan, 2018; Zhou et al, 2019), FOPID controller (Bhookya and Jatoth, 2019; Bhullar et al, 2020b), PID plus second order derivative (PIDD 2 ) controller (Mokeddem and Mirjalili, 2020; Mosaad et al, 2018) and derivatives of PID controller (Moschos and Parisses, in press; Paliwal et al, 2021) along with neural network predictive control (Elsisi, 2019) and state feedback controller (Eke et al, 2021; Gozde, 2020; Mary et al, 2021) have so far been utilized. Similar to the case in DC motors, the PID controller is the most preferred controller for an AVR system, as well (Ayas, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Performance evaluation of a novel improved slime mould algorithm for direct current motor and automatic voltage regulator systems

İzci

Ekinci

Zeynelgil

et al. 2021

Transactions of the Institute of Measurement and Control

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This study deals with the controlling the speed of a direct current (DC) motor via a fractional order proportional–integral–derivative (FOPID) controller and maintaining the terminal voltage level of an automatic voltage regulator (AVR) via a proportional–integral–derivative plus second order derivative (PIDD2) controller. To adjust the parameters of those controllers, a novel improved slime mould algorithm (ISMA) is proposed. The latter is a novel metaheuristic algorithm developed in this work. The proposed algorithm aims to improve the original SMA in terms of exploration with the aid of a modified opposition-based learning scheme and in terms of exploitation with the aid of the Nelder–Mead simplex search method. A time domain objective function, which includes time response specifications of steady state error and maximum overshoot along with rise and settling times, is used as a performance index to design the FOPID controller-based DC motor system and PIDD2 controller-based AVR system. The performance of the proposed novel approaches for both systems are assessed through time and frequency domain simulations along with statistical tests which show the greater performance of the improved algorithm. Further to this, the efficacy of the proposed approaches for both systems is compared with other available and effective approaches in the literature. The extensive comparative results demonstrate the proposed method to be superior to those state-of-the-art approaches for both DC motor speed and AVR control systems.

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Section: Literature Reviewmentioning

confidence: 99%

Performance evaluation of a novel improved slime mould algorithm for direct current motor and automatic voltage regulator systems

İzci

Ekinci

Zeynelgil

et al. 2021

Transactions of the Institute of Measurement and Control

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“…Many studies have been conducted on AVRs, which control the output voltage of synchronous generators. These are control methods performed together with various algorithms such as traditional PID implementations [9][10][11][12], cuckoo search algorithm [13], particle swarm optimization [14], coyote optimization algorithm [15], whale optimization algorithm [16,17], nonlinear robust coordinated [18], PSS and H∞ optimization [19] and kidney-inspired algorithm [20]. In addition to traditional PI and PID applications for the control of load frequencies of synchronous generators and power systems, control methods used with different algorithms, artificial intelligence and optimization techniques are also seen.…”

Section: Introductionmentioning

confidence: 99%

Design, Control and Automation of MHPP - An Experimental Setup

Altınkaya

ULU>

2022

Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım Ve Teknoloji

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In this paper the design, manufacturing and automation of a micro hydroelectric power plant (MHPP) prototype has been carried out. The experimental setup consists of three 1 kW synchronous generators (SGs) working in synchronization with each other and with the grid, three Pelton turbines with a single nozzle manufactured using a 3D printer, a water tank with a capacity of approximately one ton, a 5.5 kW centrifugal pump providing appropriate flow and head conditions and an 11 kW driver controlling the speed of this pump. The mechanical and electrical structure of the system and its working scenario are designed to be the closest to a real MHPP. S7-1200 PLC (Programmable Logic Controller) is used in order to control the voltage and frequency values of synchronous generators according to the load as well as for other control processes. In this study, PID control method is preferred for frequency and voltage control. It is possible to control and monitor the whole system through SCADA (Supervisory Control and Data Acquisition) screens. The results have been evaluated by obtaining frequency-time, voltage-time, active power-valve opening, excitation current-reactive power graphs of synchronous generators under different load conditions and in single, local and synchronous operating modes.

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“…Two [29] or three [30] higher degrees of freedom controllers have been inspected in this ground of training, which were also of the InOr type. Limited FrOr controllers that have found to be of use are FOPI [31], FOPIDN [32][33][34], and proportional with TIDN [35][36][37][38]. The literature on AGC systems provides an argument about the training of InOr amalgamated controllers (PD-PID) [39], FrOr amalgamated controllers (FOPI-FOPD) [20], and the assemblage of InOr and FrOr controllers (PIDN-FOPD).…”

Section: Introductionmentioning

confidence: 99%

Dynamic Stability Evaluation of an Integrated Biodiesel-Geothermal Power Plant-Based Power System with Spotted Hyena Optimized Cascade Controller

Saha¹,

Dash²,

Babu

et al. 2022

Sustainability

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The perception of automatic generation control (AGC) has a massive part in delivering eminence power in an interrelated structure. To acquire eminence power by monitoring the fluctuations of frequency and tie-link power, an appropriate controller strategy is essential. This work explores AGC learning under the traditional situation. In this study, we employ a cascade controller with proportional amalgamation with a tilt-integral-derivative with a filter (TIDN) and fractional order integral-derivative (FOID), named TIDN-FOID. In order to acquire the controller’s attributes, a meta-heuristic optimization algorithm spotted hyena optimizer (SHO) is employed. Several investigations express the excellency of the TIDN-FOID controller over other controllers from outlook regarding the lessened level of peak_overshoot, peak_undershoot, and settling_time for the considered structure. The structure comprises thermal, biodiesel units in area 1, thermal, and geothermal units in area-2, and hydrothermal units in area-3. Both biodiesel and GPP have a better effect on system dynamics even in the presence of time delay. Action in the redox flow battery is also examined, providing a noteworthy outcome. Eigenvalue assessment is carried out to comment on the stability of the system. TIDN-FOID parameter values at nominal conditions are appropriate for a higher disturbance value without the need for optimization.

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A novel optimal PIλDND2N2 controller using coyote optimization algorithm for an AVR system

Cited by 30 publications

References 40 publications

Performance evaluation of a novel improved slime mould algorithm for direct current motor and automatic voltage regulator systems

Performance evaluation of a novel improved slime mould algorithm for direct current motor and automatic voltage regulator systems

Design, Control and Automation of MHPP - An Experimental Setup

Dynamic Stability Evaluation of an Integrated Biodiesel-Geothermal Power Plant-Based Power System with Spotted Hyena Optimized Cascade Controller

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