Adaptive PID control based on orthogonal endocrine neural networks

Milovanović, Miroslav B.; Antić, Dragan; Milojković, Marko; Nikolić, Saša; Perić, Staniša Lj.; Spasić, Miodrag

doi:10.1016/j.neunet.2016.08.012

Cited by 31 publications

(14 citation statements)

References 33 publications

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“…Milovanović, Miroslav B. el. came up with a complex OENN-OEANFIS structure for online PID tuning which significantly reduced the signal deviations of the payload [6]. 1 12.…”

Section: Theorymentioning

confidence: 99%

Improving PID Control Based on Neural Network

Gómez-Espinosa

2018

2018 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

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PID is a prevalent tool of automatic control in both industry and home environment, and PID parameters are often forced to modify because of systematic service on the machines or systems, which is time-costing. The project aims to investigate the possibility of applying neural network and reducing PID configuration in controlling industry process, by means of establishing control models and comparing control performance between conventional PID method and improved PID control based on neural network where two built neural networks are considered as cores to adjust weights which result in the suggested PID parameters. Adaptive learning rate is also applied which is adjusted by the algorithm based on the error changes. Algorithm program is written in Siemens TIA Portal and simulated in Factory I/O. In general, the simulations after analysis have shown that the proposed model has a better performance than conventional PID in terms of steady state, deviations and consistency of control value except tuning time. In the future the author is dedicated to continue improving the mentioned model through quickening learning process, applying better activation function and modifying variable structure and so on.

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“…Milovanović, Miroslav B. el. came up with a complex OENN-OEANFIS structure for online PID tuning which significantly reduced the signal deviations of the payload [6]. 1 12.…”

Section: Theorymentioning

confidence: 99%

Improving PID Control Based on Neural Network

Gómez-Espinosa

2018

2018 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

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“…The plan is to introduce new, modern teaching units in the field of artificial intelligence and intelligent control that follow the latest technological innovations in the IT world. The changes will be implemented by a group of teachers with competences in the field of modern information technology, which are reflected in the large number of papers in leading journals dealing with artificial intelligence (neural networks, fuzzy logic, genetic algorithms) [2][3][4]. Currently, the process of accreditation of study programs at the Faculty of Electronic Engineering is in progress, so all planned innovations of the courses will be announced within the new curriculum of these courses in the new accreditation.…”

Section: Human and Materials Resourcesmentioning

confidence: 99%

Implementation of Modern Intelligent Control Methods Within the Control Systems Study Module

et al. 2018

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This paper presents an innovative project “Implementation of Modern Intelligent Control Methods within the Study Module Control Systems” which is selected to be financed by Serbian Ministry of Education, Science and Technological Development. The project is part of a public call for projects “Development of Higher Education” and it will be realized during a school year 2018/2019. In this paper, the main goals of the project are presented and project activities and expected results are defined. Finally, three courses which are selected to be innovated through the project activities are presented in the terms of lecture topics and teaching methods.

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“…One of the most important applications of orthogonal polynomials is designing orthogonal filters. Today, these filters become an efficient tool for identification, modelling and control of dynamical systems [9][10][11][12][13].…”

Section: Generalized Quasi-orthogonal Polynomialsmentioning

confidence: 99%

Orthogonal Hybrid-Fuzzy Controllers

et al. 2017

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Abstract. The main idea of this paper is to present a possibility of application of hybrid-fuzzy controllers in control systems theory. In this paper, we have described a new method оf using orthogonal functions in control of dynamical systems. These functions generate genarilzed quasi-orthogonal filter, which are used in the concluding phase of the fuzzy controllers. Proposed hybrid-fuzzy controllers of Takagi-Sugeno type has been applied to a DC servo drive system and performed experiments have verified efficiency and improvements of a new control method.

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Adaptive PID control based on orthogonal endocrine neural networks

Cited by 31 publications

References 33 publications

Improving PID Control Based on Neural Network

Improving PID Control Based on Neural Network

Implementation of Modern Intelligent Control Methods Within the Control Systems Study Module

Orthogonal Hybrid-Fuzzy Controllers

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