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Fractional order PIλDμ controller with optimal parameters using Modified Grey Wolf Optimizer for AVR system

Verma Santosh Kumar, Devarapalli Ramesh

Archives of Control Sciences

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2022

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Vol. 32, No. 2

429--450

EN

In this paper, an automatic voltage regulator (AVR) embedded with fractional order PID (FOPID) is employed for the alternator terminal voltage control. A novel meta-heuristic technique, a modified version of grey wolf optimizer (mGWO) is proposed to design and optimize the FOPID AVR system. The parameters of FOPID, namely, proportional gain (ΚP), the integral gain ( ΚI), the derivative gain ( ΚD), λ and μ have been optimally tuned with the proposed mGWO technique using a novel fitness function. The initial values of the ΚP, ΚI , and ΚD of the FOPID controller are obtained using Ziegler-Nichols (ZN) method, whereas the initial values of λ and μ have been chosen as arbitrary values. The proposed algorithm offers more benefits such as easy implementation, fast convergence characteristics, and excellent computational ability for the optimization of functions with more than three variables. Additionally, the hasty tuning of FOPID controller parameters gives a high-quality result, and the proposed controller also improves the robustness of the system during uncertainties in the parameters. The quality of the simulated result of the proposed controller has been validatedby other state-of-the-art techniques in the literature.

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Prediction of blast-induced ground vibration using GPR and blast-design parameters optimization based on novel grey-wolf optimization algorithm

Lawal A. I., Olajuyi S. I., Kwon S., Aladejare A. E., Edo T. M.

Acta Geophysica

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2021

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Vol. 69, no. 4

1313--1324

EN

Blasting is an intrinsic component of mining cycle of operation. However, it is usually associated with negative environmental efects such as blast-induced ground vibration (BIGV) which require accurate prediction and control. Therefore, in this study, Gaussian process regression (GPR) has been proposed for prediction of BIGV in terms of peak particle velocity (PPV), while grey-wolf optimization (GWO) algorithm has been used to optimize the blast-design parameters for the control of BIGV in Obajana limestone quarry, Nigeria. The blast-design parameters such as burden (B), spacing (S), hole depth (Hd), stemming length (T), and number of holes (nh) were obtained from the quarry. The distance from the blasting point to the measuring point (D) and the charge per delay (W) were measured and determined, respectively. The PPV was also measured for the number of blasting operations witnessed. These seven parameters were used as inputs to the proposed GPR model, while the PPV was the targeted output. The performance of the proposed model was evaluated using some statistical indices. The output of the GPR model was compared with ANN model and three empirical models, and the GPR model proved to be more accurate with the coefcient of determination (R2 ) of approximately 1 and variance accounted for VAF of about 100%, respectively. In addition, the GWO was also developed to select the optimum blasting parameters using the ANN model for the generation of objective function. The output of the GWO revealed that if the number of holes (nh) can be reduced by 45% and W by 8%, the PPV will be reduced by about 94%. Hence, the proposed models are both suitable for prediction of PPV and optimization of blast-design parameters.

3

Zastosowanie algorytmu Grey Wolf Optimizer w optymalizacji nastaw regulatora stanu układu trójmasowego

Żychlewicz M.

Interdisciplinary Journal of Engineering Sciences

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2018

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Vol. 6, no. 1

12--20

PL

W artykule przedstawiono układ regulacji prędkości napędu złożonego napędu elektrycznego, uwzględniającego podwójne połączenie sprężyste. W nadrzędnej pętli sterowania zaimplementowano regulator stanu. Głównym elementem pracy jest optymalizacja parametrów zewnętrznej części układu za pomocą algorytmu metaheurystycznego GWO (Grey Wolf Optimizer). Zaprojektowana w ten sposób struktura sterowania została porównana z klasycznym rozwiązaniem projektowym, w którym zastosowano metodę rozłożenia biegunów równania charakterystycznego do wyznaczania nastaw regulatora. Uzyskano wysoką precyzję odtwarzania sygnału zadanego. Przeprowadzona została również analiza działania struktury sterowania w obecności zmian parametrów układu trójmasowego. Przedstawione rozważania teoretyczne zostały potwierdzone w testach obliczeniowych.

EN

This article presents control structure of complex drive that contains two elastic couplings. In the outer control loop the state space controller was implemented. The main point of described work is optimization of parameters used in this part of the drive using metaheuristic algorithm called GWO (Grey Wolf Optimizer). The control structure, designed using mentioned optimization method, was compared to classic solution, known from control theory. High precision of reference speed tracking was achieved. An analysis of the system in the presence of mechanical parameters changes was also prepared. Theoretical considerations were confirmed in numerical tests.