Random Search Optimization Approach for Human-Robot Systems Modeling

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Random Search Optimization Approach for Human-Robot Systems Modeling. / Зайцева, Юлия Сергеевна ; Кузнецов, Николай Владимирович ; Андриевский, Борис Ростиславич.

2022. 267-271 Работа представлена на 2022 International Russian Automation Conference (RusAutoCon), Sochi, Российская Федерация.

Результаты исследований: Материалы конференций › материалы › Рецензирование

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Зайцева, ЮС , Кузнецов, НВ & Андриевский, БР 2022, 'Random Search Optimization Approach for Human-Robot Systems Modeling', Работа представлена на 2022 International Russian Automation Conference (RusAutoCon), Sochi, Российская Федерация, 4/09/22 - 10/09/22 стр. 267-271. https://doi.org/10.1109/rusautocon54946.2022.9896330

BibTeX

@conference{970dd01d62104fdb8167630b93aeabb3,

title = "Random Search Optimization Approach for Human-Robot Systems Modeling",

abstract = "Human operator behavior in manual control of any electro-mechanical system can be complex and varied. It is possible to single out human operator behavior well described by linear differential equations. It allows for studying many tasks of monotonous manual control, such as tracking a reference signal. The analysis of such a system forms the basis for understanding its stability and controllability features. It is necessary to know the parameters of the human operator model for studying and designing such a system, which may depend on the parameters of the plant. This paper proposes an approach to human operator parameters calculation in manual control systems based on derivative-free optimization method. For three coefficients of the PID controller, the parameters of the human operator model were calculated using the proposed algorithm in MATLAB/Simulink. The evolution of the system parameters in the process of searching for the extremum of the selected function is illustrated graphically. The proposed method can be applied as part of the robot's intelligent control in real-time.",

keywords = "actuator saturation, human operator, human robot interaction, learning, manual control, pid, random search",

author = "Зайцева, {Юлия Сергеевна} and Кузнецов, {Николай Владимирович} and Андриевский, {Борис Ростиславич}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; null ; Conference date: 04-09-2022 Through 10-09-2022",

year = "2022",

month = sep,

day = "4",

doi = "10.1109/rusautocon54946.2022.9896330",

language = "English",

pages = "267--271",

}

RIS

TY - CONF

T1 - Random Search Optimization Approach for Human-Robot Systems Modeling

AU - Зайцева, Юлия Сергеевна

AU - Кузнецов, Николай Владимирович

AU - Андриевский, Борис Ростиславич

PY - 2022/9/4

Y1 - 2022/9/4

N2 - Human operator behavior in manual control of any electro-mechanical system can be complex and varied. It is possible to single out human operator behavior well described by linear differential equations. It allows for studying many tasks of monotonous manual control, such as tracking a reference signal. The analysis of such a system forms the basis for understanding its stability and controllability features. It is necessary to know the parameters of the human operator model for studying and designing such a system, which may depend on the parameters of the plant. This paper proposes an approach to human operator parameters calculation in manual control systems based on derivative-free optimization method. For three coefficients of the PID controller, the parameters of the human operator model were calculated using the proposed algorithm in MATLAB/Simulink. The evolution of the system parameters in the process of searching for the extremum of the selected function is illustrated graphically. The proposed method can be applied as part of the robot's intelligent control in real-time.

AB - Human operator behavior in manual control of any electro-mechanical system can be complex and varied. It is possible to single out human operator behavior well described by linear differential equations. It allows for studying many tasks of monotonous manual control, such as tracking a reference signal. The analysis of such a system forms the basis for understanding its stability and controllability features. It is necessary to know the parameters of the human operator model for studying and designing such a system, which may depend on the parameters of the plant. This paper proposes an approach to human operator parameters calculation in manual control systems based on derivative-free optimization method. For three coefficients of the PID controller, the parameters of the human operator model were calculated using the proposed algorithm in MATLAB/Simulink. The evolution of the system parameters in the process of searching for the extremum of the selected function is illustrated graphically. The proposed method can be applied as part of the robot's intelligent control in real-time.

KW - actuator saturation

KW - human operator

KW - human robot interaction

KW - learning

KW - manual control

KW - pid

KW - random search

UR - http://www.scopus.com/inward/record.url?scp=85140873986&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/bcca0b0f-798b-3ff0-99c1-9c76c0ed09a1/

U2 - 10.1109/rusautocon54946.2022.9896330

DO - 10.1109/rusautocon54946.2022.9896330

M3 - Paper

SP - 267

EP - 271

Y2 - 4 September 2022 through 10 September 2022

ER -

ID: 100349137

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