Research on profiling tracking control optimization of orchard sprayer based on the phenotypic characteristics of tree crown
•A dynamic threshold function is introduced to improve CMAC-PID algorithm.•The optimization parameters of the dynamic threshold function were determined.•The response speed of the control system was obviously improved.•The average error of profiling tracking control has been reduced by 35.9% at leas...
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| Veröffentlicht in: | Computers and electronics in agriculture 2022-01, Vol.192, p.106455, Article 106455 |
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| container_title | Computers and electronics in agriculture |
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| creator | Nan, Yulong Zhang, Huichun Zheng, Jiaqiang Yang, Kunqi Yang, Weikang Zhang, Meng |
| description | •A dynamic threshold function is introduced to improve CMAC-PID algorithm.•The optimization parameters of the dynamic threshold function were determined.•The response speed of the control system was obviously improved.•The average error of profiling tracking control has been reduced by 35.9% at least.
The performance of the profiling tracking control system was one of the important factors affecting the spray deposition and drift characteristics of the profiling variable spray. This paper proposed a dynamic threshold function to improve the CMAC-PID control algorithm to improve the real-time response speed and robustness of profiling tracking control system. The optimal parameters of dynamic threshold function was determined through a response surface experiment and optimal calculation. The continuous profiling tracking experiment results for outdoor tree canopy within 0–2.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm adopted by the profiling control system, the rise time was respectively shortened by 71.5%, 66.1% and 67.3%, the adjustment time was respectively shortened by 67.6%, 57.6% and 50.0%, and the overshoot was respectively 0.658%, 0.552% and 3.46% for the profiling angle position step response of the profiling mechanism module A_up, B and A_down. The continuous profiling tracking experiment results for outdoor tree canopy within 2.5–11.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm was adopted by the profiling control system, the profiling tracking response curves and the profiling target angle curves were closer to coincidence, and the average error of profiling tracking has been reduced by 35.9%, 57.4% and 38.1% respectively for the profiling mechanism module A_up, B and A_down. It showed that the profiling control system using the improved CMAC-PID algorithm had better response speed and profiling tracking performance. |
| doi_str_mv | 10.1016/j.compag.2021.106455 |
| format | Article |
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The performance of the profiling tracking control system was one of the important factors affecting the spray deposition and drift characteristics of the profiling variable spray. This paper proposed a dynamic threshold function to improve the CMAC-PID control algorithm to improve the real-time response speed and robustness of profiling tracking control system. The optimal parameters of dynamic threshold function was determined through a response surface experiment and optimal calculation. The continuous profiling tracking experiment results for outdoor tree canopy within 0–2.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm adopted by the profiling control system, the rise time was respectively shortened by 71.5%, 66.1% and 67.3%, the adjustment time was respectively shortened by 67.6%, 57.6% and 50.0%, and the overshoot was respectively 0.658%, 0.552% and 3.46% for the profiling angle position step response of the profiling mechanism module A_up, B and A_down. The continuous profiling tracking experiment results for outdoor tree canopy within 2.5–11.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm was adopted by the profiling control system, the profiling tracking response curves and the profiling target angle curves were closer to coincidence, and the average error of profiling tracking has been reduced by 35.9%, 57.4% and 38.1% respectively for the profiling mechanism module A_up, B and A_down. It showed that the profiling control system using the improved CMAC-PID algorithm had better response speed and profiling tracking performance.</description><identifier>ISSN: 0168-1699</identifier><identifier>EISSN: 1872-7107</identifier><identifier>DOI: 10.1016/j.compag.2021.106455</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Algorithms ; Canopies ; CMAC neural network ; Control algorithms ; Control systems ; Control theory ; Dynamic threshold ; Experiments ; Mathematical analysis ; Modules ; Optimization ; Profiling control ; Profiling mechanism ; Profiling spray ; Proportional integral derivative ; Response surface methodology ; Robust control ; Spray deposition ; Step response ; Time response ; Tracking control</subject><ispartof>Computers and electronics in agriculture, 2022-01, Vol.192, p.106455, Article 106455</ispartof><rights>2021 Elsevier B.V.</rights><rights>Copyright Elsevier BV Jan 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c334t-c7750555d7b0049757c3ca6cbe8253819081851eedaedf3f39aa734576f6ea653</citedby><cites>FETCH-LOGICAL-c334t-c7750555d7b0049757c3ca6cbe8253819081851eedaedf3f39aa734576f6ea653</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0168169921004725$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Nan, Yulong</creatorcontrib><creatorcontrib>Zhang, Huichun</creatorcontrib><creatorcontrib>Zheng, Jiaqiang</creatorcontrib><creatorcontrib>Yang, Kunqi</creatorcontrib><creatorcontrib>Yang, Weikang</creatorcontrib><creatorcontrib>Zhang, Meng</creatorcontrib><title>Research on profiling tracking control optimization of orchard sprayer based on the phenotypic characteristics of tree crown</title><title>Computers and electronics in agriculture</title><description>•A dynamic threshold function is introduced to improve CMAC-PID algorithm.•The optimization parameters of the dynamic threshold function were determined.•The response speed of the control system was obviously improved.•The average error of profiling tracking control has been reduced by 35.9% at least.
The performance of the profiling tracking control system was one of the important factors affecting the spray deposition and drift characteristics of the profiling variable spray. This paper proposed a dynamic threshold function to improve the CMAC-PID control algorithm to improve the real-time response speed and robustness of profiling tracking control system. The optimal parameters of dynamic threshold function was determined through a response surface experiment and optimal calculation. The continuous profiling tracking experiment results for outdoor tree canopy within 0–2.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm adopted by the profiling control system, the rise time was respectively shortened by 71.5%, 66.1% and 67.3%, the adjustment time was respectively shortened by 67.6%, 57.6% and 50.0%, and the overshoot was respectively 0.658%, 0.552% and 3.46% for the profiling angle position step response of the profiling mechanism module A_up, B and A_down. The continuous profiling tracking experiment results for outdoor tree canopy within 2.5–11.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm was adopted by the profiling control system, the profiling tracking response curves and the profiling target angle curves were closer to coincidence, and the average error of profiling tracking has been reduced by 35.9%, 57.4% and 38.1% respectively for the profiling mechanism module A_up, B and A_down. It showed that the profiling control system using the improved CMAC-PID algorithm had better response speed and profiling tracking performance.</description><subject>Algorithms</subject><subject>Canopies</subject><subject>CMAC neural network</subject><subject>Control algorithms</subject><subject>Control systems</subject><subject>Control theory</subject><subject>Dynamic threshold</subject><subject>Experiments</subject><subject>Mathematical analysis</subject><subject>Modules</subject><subject>Optimization</subject><subject>Profiling control</subject><subject>Profiling mechanism</subject><subject>Profiling spray</subject><subject>Proportional integral derivative</subject><subject>Response surface methodology</subject><subject>Robust control</subject><subject>Spray deposition</subject><subject>Step response</subject><subject>Time response</subject><subject>Tracking control</subject><issn>0168-1699</issn><issn>1872-7107</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLAzEYRYMoWKv_wEXA9dRkMnnMRpDiCwqC6DqkmW_a1HYyJqlS8cebYVy7yoNzbvJdhC4pmVFCxfVmZv2uN6tZSUqar0TF-RGaUCXLQlIij9EkY6qgoq5P0VmMG5LPtZIT9PMCEUywa-w73Affuq3rVjgFY9-HjfVdCn6LfZ_czn2b5DLnW-yzYkKDYx_MAQJemgjNkJHWgPs1dD4demfxQBmbILiYnI2DmgIAtsF_defopDXbCBd_6xS93d-9zh-LxfPD0_x2UVjGqlRYKTnhnDdySUhVSy4ts0bYJaiSM0VroqjiFKAx0LSsZbUxklVcilaAEZxN0dWYmwf82ENMeuP3octP6lKUWedS1ZmqRir_LcYAre6D25lw0JTooWe90WPPeuhZjz1n7WbUIE_w6SDoaB10FhoXwCbdePd_wC8iFoqh</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Nan, Yulong</creator><creator>Zhang, Huichun</creator><creator>Zheng, Jiaqiang</creator><creator>Yang, Kunqi</creator><creator>Yang, Weikang</creator><creator>Zhang, Meng</creator><general>Elsevier B.V</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>202201</creationdate><title>Research on profiling tracking control optimization of orchard sprayer based on the phenotypic characteristics of tree crown</title><author>Nan, Yulong ; Zhang, Huichun ; Zheng, Jiaqiang ; Yang, Kunqi ; Yang, Weikang ; Zhang, Meng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c334t-c7750555d7b0049757c3ca6cbe8253819081851eedaedf3f39aa734576f6ea653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Canopies</topic><topic>CMAC neural network</topic><topic>Control algorithms</topic><topic>Control systems</topic><topic>Control theory</topic><topic>Dynamic threshold</topic><topic>Experiments</topic><topic>Mathematical analysis</topic><topic>Modules</topic><topic>Optimization</topic><topic>Profiling control</topic><topic>Profiling mechanism</topic><topic>Profiling spray</topic><topic>Proportional integral derivative</topic><topic>Response surface methodology</topic><topic>Robust control</topic><topic>Spray deposition</topic><topic>Step response</topic><topic>Time response</topic><topic>Tracking control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nan, Yulong</creatorcontrib><creatorcontrib>Zhang, Huichun</creatorcontrib><creatorcontrib>Zheng, Jiaqiang</creatorcontrib><creatorcontrib>Yang, Kunqi</creatorcontrib><creatorcontrib>Yang, Weikang</creatorcontrib><creatorcontrib>Zhang, Meng</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers and electronics in agriculture</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nan, Yulong</au><au>Zhang, Huichun</au><au>Zheng, Jiaqiang</au><au>Yang, Kunqi</au><au>Yang, Weikang</au><au>Zhang, Meng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Research on profiling tracking control optimization of orchard sprayer based on the phenotypic characteristics of tree crown</atitle><jtitle>Computers and electronics in agriculture</jtitle><date>2022-01</date><risdate>2022</risdate><volume>192</volume><spage>106455</spage><pages>106455-</pages><artnum>106455</artnum><issn>0168-1699</issn><eissn>1872-7107</eissn><abstract>•A dynamic threshold function is introduced to improve CMAC-PID algorithm.•The optimization parameters of the dynamic threshold function were determined.•The response speed of the control system was obviously improved.•The average error of profiling tracking control has been reduced by 35.9% at least.
The performance of the profiling tracking control system was one of the important factors affecting the spray deposition and drift characteristics of the profiling variable spray. This paper proposed a dynamic threshold function to improve the CMAC-PID control algorithm to improve the real-time response speed and robustness of profiling tracking control system. The optimal parameters of dynamic threshold function was determined through a response surface experiment and optimal calculation. The continuous profiling tracking experiment results for outdoor tree canopy within 0–2.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm adopted by the profiling control system, the rise time was respectively shortened by 71.5%, 66.1% and 67.3%, the adjustment time was respectively shortened by 67.6%, 57.6% and 50.0%, and the overshoot was respectively 0.658%, 0.552% and 3.46% for the profiling angle position step response of the profiling mechanism module A_up, B and A_down. The continuous profiling tracking experiment results for outdoor tree canopy within 2.5–11.5 s showed that, compared with the CMAC-PID control algorithm, when the improved CMAC-PID control algorithm was adopted by the profiling control system, the profiling tracking response curves and the profiling target angle curves were closer to coincidence, and the average error of profiling tracking has been reduced by 35.9%, 57.4% and 38.1% respectively for the profiling mechanism module A_up, B and A_down. It showed that the profiling control system using the improved CMAC-PID algorithm had better response speed and profiling tracking performance.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.compag.2021.106455</doi></addata></record> |
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| subjects | Algorithms Canopies CMAC neural network Control algorithms Control systems Control theory Dynamic threshold Experiments Mathematical analysis Modules Optimization Profiling control Profiling mechanism Profiling spray Proportional integral derivative Response surface methodology Robust control Spray deposition Step response Time response Tracking control |
| title | Research on profiling tracking control optimization of orchard sprayer based on the phenotypic characteristics of tree crown |
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