Research on tool control system of double cutters experimental platform based on fuzzy neural network predictive control
According to the characteristics of the tool hydraulic control system of the double cutters experimental pplatform, intelligent control methodology forecasted by fuzzy neural network is introduced into the control system. The two level control systems of fuzzy neural network predictive control and f...
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| Veröffentlicht in: | Journal of intelligent & fuzzy systems 2021-01, Vol.40 (1), p.65-76 |
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| container_end_page | 76 |
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| container_title | Journal of intelligent & fuzzy systems |
| container_volume | 40 |
| creator | Zhou, Peng Tian, Junxing Sun, Jian Yao, Jinmei Zou, Defang Yu, Wenda |
| description | According to the characteristics of the tool hydraulic control system of the double cutters experimental pplatform, intelligent control methodology forecasted by fuzzy neural network is introduced into the control system. The two level control systems of fuzzy neural network predictive control and fuzzy control are designed. The fuzzy neural network predictive controller mainly completes the analysis and control of the speed and pressure in the tool hydraulic system. The speed control signal and pressure control signal from the first level are output to the fuzzy controller. Then, through logical reasoning, the control signal is output and the actuator is driven by the fuzzy controller to complete the control function of the tool system. In this paper, compared with the traditional PID control, the fuzzy neural network predictive control technology has better control accuracy, dynamic response performance and steady-state accuracy. The fuzzy neural network predictive control technology can be used to control the tool hydraulic system of Tunnel Boring Machine. |
| doi_str_mv | 10.3233/JIFS-182804 |
| format | Article |
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The two level control systems of fuzzy neural network predictive control and fuzzy control are designed. The fuzzy neural network predictive controller mainly completes the analysis and control of the speed and pressure in the tool hydraulic system. The speed control signal and pressure control signal from the first level are output to the fuzzy controller. Then, through logical reasoning, the control signal is output and the actuator is driven by the fuzzy controller to complete the control function of the tool system. In this paper, compared with the traditional PID control, the fuzzy neural network predictive control technology has better control accuracy, dynamic response performance and steady-state accuracy. The fuzzy neural network predictive control technology can be used to control the tool hydraulic system of Tunnel Boring Machine.</description><identifier>ISSN: 1064-1246</identifier><identifier>EISSN: 1875-8967</identifier><identifier>DOI: 10.3233/JIFS-182804</identifier><language>eng</language><publisher>Amsterdam: IOS Press BV</publisher><subject>Actuators ; Artificial neural networks ; Boring machines ; Boring tools ; Cognition & reasoning ; Control methods ; Control systems ; Controllers ; Cutters ; Dynamic response ; Fuzzy control ; Fuzzy logic ; Fuzzy systems ; Hydraulic control ; Hydraulic equipment ; Hydraulics ; Neural networks ; Predictive control ; Proportional integral derivative ; Speed control ; Tunnel construction</subject><ispartof>Journal of intelligent & fuzzy systems, 2021-01, Vol.40 (1), p.65-76</ispartof><rights>Copyright IOS Press BV 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c261t-edc6990baf171dc4e2eb75bff49c92567754af2a51d7907bbca3cc226ee403e53</citedby><cites>FETCH-LOGICAL-c261t-edc6990baf171dc4e2eb75bff49c92567754af2a51d7907bbca3cc226ee403e53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Zhou, Peng</creatorcontrib><creatorcontrib>Tian, Junxing</creatorcontrib><creatorcontrib>Sun, Jian</creatorcontrib><creatorcontrib>Yao, Jinmei</creatorcontrib><creatorcontrib>Zou, Defang</creatorcontrib><creatorcontrib>Yu, Wenda</creatorcontrib><title>Research on tool control system of double cutters experimental platform based on fuzzy neural network predictive control</title><title>Journal of intelligent & fuzzy systems</title><description>According to the characteristics of the tool hydraulic control system of the double cutters experimental pplatform, intelligent control methodology forecasted by fuzzy neural network is introduced into the control system. The two level control systems of fuzzy neural network predictive control and fuzzy control are designed. The fuzzy neural network predictive controller mainly completes the analysis and control of the speed and pressure in the tool hydraulic system. The speed control signal and pressure control signal from the first level are output to the fuzzy controller. Then, through logical reasoning, the control signal is output and the actuator is driven by the fuzzy controller to complete the control function of the tool system. In this paper, compared with the traditional PID control, the fuzzy neural network predictive control technology has better control accuracy, dynamic response performance and steady-state accuracy. 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| source | EBSCOhost Business Source Complete |
| subjects | Actuators Artificial neural networks Boring machines Boring tools Cognition & reasoning Control methods Control systems Controllers Cutters Dynamic response Fuzzy control Fuzzy logic Fuzzy systems Hydraulic control Hydraulic equipment Hydraulics Neural networks Predictive control Proportional integral derivative Speed control Tunnel construction |
| title | Research on tool control system of double cutters experimental platform based on fuzzy neural network predictive control |
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