A new LQG optimal control strategy applied on a hybrid wind turbine/solid oxide fuel cell/ in the presence of the interval uncertainties

Yu, Dongmin; Mao, Yuhong; Bing, Gu; Nojavan, Sayyad; Jermsittiparsert, Kittisak; Nasseri, Maryam

doi:10.1016/j.segan.2019.100296

Cited by 54 publications

(22 citation statements)

References 19 publications

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“…In other words, a swarm intelligence optimization algorithm with high performance can greatly improve the results of MIS. Complex feature spaces often are challenging enough to be dealt with [ 18 , 19 ], especially in the medical area [ 20 ]. Hence, more attention should be paid to the accuracy and efficacy of the procedure used to tackle the model [ 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

Ant colony optimization with Cauchy and greedy Levy mutations for multilevel COVID 19 X-ray image segmentation

Liu

Zhao

et al. 2021

Computers in Biology and Medicine

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This paper focuses on the study of multilevel COVID-19 X-ray T image segmentation based on swarm intelligence optimization to improve the diagnostic level of COVID-19. We present the first ant colony optimization with the Cauchy mutation and the greedy Levy mutation, termed CLACO, for continuous domains. Specifically, the Cauchy mutation is applied to the end phase of ant foraging in CLACO to enhance its searchability and to boost its convergence rate. The greedy Levy mutation is applied to the optimal ant individuals to confer an improved ability to jump out of the local optimum. Furthermore, this paper develops a novel CLACO-based multilevel image segmentation method, termed CLACO-MIS. Using 2D Kapur's entropy as the CLACO fitness function based on 2D histograms consisting of non-local mean filtered images and grayscale images, CLACO-MIS was succefully applied to the segmentation of COVID-19 X-ray images. A comparison of CLACO with some relevant variants and other excellent peers on 30 benchmark functions from IEEE CEC2014 demonstrates the superior performance of CLACO in terms of search capability, and convergence speed as well as ability to jump out of the local optimum. Moreover, CLACO-MIS was shown to have a better segmentation effect and a stronger adaptability at different threshold levels than other methods in performing segmentation experiments of COVID-19 X-ray images. Therefore, CLACO-MIS has great potential to be used for improving the diagnostic level of COVID-19. This research will host a webservice for any question at https://aliasgharheidari.com .

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Section: Introductionmentioning

confidence: 99%

Ant colony optimization with Cauchy and greedy Levy mutations for multilevel COVID 19 X-ray image segmentation

Liu

Zhao

et al. 2021

Computers in Biology and Medicine

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“…Energy systems have been facing problems such as inflating consumption cost [1] and greenhouse gas (GHG) emission [2][3][4], as well as network overloading [2,[5][6][7][8][9][10][11]. e conventional grid may not resolve these problems; however, a smart distribution system (DS) equipped with DGs and demand response (DR) has the potential to overcome these issues.…”

Section: Introductionmentioning

confidence: 99%

Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

Muqeet

Munir

Ahmad

et al. 2021

Mathematical Problems in Engineering

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Present power systems face problems such as rising energy charges and greenhouse gas (GHG) releases. These problems may be assuaged by participating distributed generators (DGs) and demand response (DR) policies in the distribution system (DS). The main focus of this paper is to propose an energy management system (EMS) approach for campus microgrid (µG). For this purpose, a Pakistani university has been investigated and an optimal solution has been proposed. Conventionally, it contains electricity from the national grid only as a supply to fulfil the energy demand. Under the proposed setup, it contains campus owned nondispatchable DGs such as solar photovoltaic (PV) panels and microturbines (MTs) as dispatchable sources. To overcome the random nature of solar irradiance, station battery has been integrated as energy storage. The subsequent nonlinear mathematical problem has been scheduled by mixed-integer nonlinear programming (MINLP) in MATLAB for saving energy cost and battery aging cost. The framework has been validated under deterministic and stochastic environments. Among random parameters, solar irradiance and load have been taken into consideration. Case studies have been carried out considering the demand response strategies to analyze the proposed model. The obtained results show that optimal management and scheduling of storage in the presence of DGs mutually benefit by minimizing consumption cost (customer) and grid load (utility) which show the efficacy of the proposed model. The results obtained are compared to the existing literature and a significant cost reduction is found.

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“…Nowadays, attention to robust approaches in nonlinear, uncertain, and disturbed systems in various applications has increased dramatically (Shi et al, 2017;Wang, Zhu, et al, 2020;Wu et al, 2019;Xiong et al, 2016;Yu et al, 2020;Zhu et al, 2020). In the case of multi-agent systems, typical shared overall behaviours under cooperative control contain consensus (Chen et al, 2016;Feng et al, 2016;Hu et al, 2016;Wen et al, 2014), synchronization (Arenas et al, 2008;Lü et al, 2004;Pecora & Carroll, 1998), flocking…”

Section: Introductionmentioning

confidence: 99%

Leader–follower consensus control for a nonlinear multi-agent robot system with input saturation and external disturbance

Naserian

Ramazani

Khaki‐Sedigh

et al. 2021

Systems Science & Control Engineering

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This paper addresses the leader-follower consensus control problem for a nonlinear multi-agent robot system with control input constraint and external disturbances. Robot system is one of the most important practical systems in the industry. Due to the presence of disturbances in most practical systems, this paper considers the issue of finite-time leader-follower consensus control of the nonlinear multi-agent robot system along with actuator saturation and bounded disturbance. The modified terminal sliding mode control method is suggested for the system which is able to guarantee the stability of the overall system and fast finite-time leader-follower consensus control. For two different scenarios, the simulation of multi-agent robot system has been performed. The results show the effectiveness of the proposed control method.

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A new LQG optimal control strategy applied on a hybrid wind turbine/solid oxide fuel cell/ in the presence of the interval uncertainties

Cited by 54 publications

References 19 publications

Ant colony optimization with Cauchy and greedy Levy mutations for multilevel COVID 19 X-ray image segmentation

Ant colony optimization with Cauchy and greedy Levy mutations for multilevel COVID 19 X-ray image segmentation

Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

Leader–follower consensus control for a nonlinear multi-agent robot system with input saturation and external disturbance

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