Using DarkNet models and metaheuristic optimization methods together to detect weeds growing along with seedlings

In the present paper we introduce an approach to implementing parallel metaheuristic optimization frameworks which is used in the design of the framework HeO. This experimental cross-platform framework is a collection of popular optimization methods implemented in C++ as algorithmic skeletons. The key feature of the discussed approach is the wide usage of metaprogramming and design patterns which allow to increase the reusability of the code and ease the process of hybrid algorithms construction for the end-user. We consider framework structure and implementation details and provide the results of numerical experiments for some well-known optimization problems.

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PID Controller Gains Tuning Using Metaheuristic Optimization Methods: A survey

International Journal of Computers ◽

10.46300/9108.2020.14.14 ◽

2020 ◽

Vol 14 ◽

Keyword(s):

Pid Controller ◽

Control Process ◽

Optimization Methods ◽

Industrial Applications ◽

Pid Controllers ◽

Pid Tuning ◽

Metaheuristic Optimization ◽

Pid Controller Tuning ◽

Vital Component

In nowadays industry, most processes are controlled and automated. Interestingly, PID controllers are major contributors to the control process since they were invented and become quite practical. PID controllers are vital component in the industry and enhancing the component will show an echo effect in today’s technology. Their drawbacks are tuning them for an application, and this provides inspiration to develop advanced optimization methods in tuning PID controllers. This survey aims to review metaheuristic optimization methods of PID controller tuning that were published between 2010 and 2018. The paper was constructed based on 22 research papers and found that 8 metaheuristics optimization methods were used with PID tuning on 5 industrial applications. The papers also extensively provided answers to 3 research questions and assessing the quality of the papers based on 6 parameters.

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Harmonic Elimination of Cascaded Multilevel Inverter using Metaheuristic Optimization Methods

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.15.23005 ◽

2018 ◽

Vol 7 (4.15) ◽

pp. 272 ◽

Cited By ~ 1

Author(s):

Srikanta Kumar Dash ◽

Byamakesh Nayak ◽

Jiban Ballav Sahu ◽

Rojalin Rout

Keyword(s):

Harmonic Distortion ◽

Optimization Methods ◽

Optimization Method ◽

Multilevel Inverter ◽

Computational Time ◽

Local Minima ◽

Metaheuristic Optimization ◽

Harmonic Elimination ◽

Whale Optimization ◽

Cascaded Multilevel Inverter

The harmonic elimination of multilevel inverters is a complicated task that includes nonlinear transcendental equations. With the increase in the level of the multilevel inverter, the no of variables of the equation also increases which makes the problem more complicated. Metaheuristic optimization algorithms play an important role in finding out optimum switching angles required for elimination of harmonics in a lesser computational time avoiding multiple local minima. This paper deals with the harmonic elimination of cascaded multilevel inverter using whale optimization algorithm. The whale optimization method has the ability to escape local minima and it takes less time of computation of results. Results are verified theoretically by taking an example of a 15-level cascaded H-bridge inverter fed from equal d.c.sources. The above scheme well minimizes lower order harmonics and gives better output voltage and a low total harmonic distortion.

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