Design and Experimental Verification of Real-Time Nonlinear Predictive Controller for Improving the Stability of Production Vehicles
Vehicle stability control under extreme conditions is influenced by the coupled nonlinear characteristics of vehicle dynamics, corresponding safety constraints, and rapid response requirements. To address these problems, this brief proposes a real-time nonlinear predictive controller for a distribut...
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| Veröffentlicht in: | IEEE transactions on control systems technology 2021-09, Vol.29 (5), p.2206-2213 |
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| container_title | IEEE transactions on control systems technology |
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| creator | Wang, Ping Liu, Hanghang Guo, Lulu Zhang, Lin Ding, Haitao Chen, Hong |
| description | Vehicle stability control under extreme conditions is influenced by the coupled nonlinear characteristics of vehicle dynamics, corresponding safety constraints, and rapid response requirements. To address these problems, this brief proposes a real-time nonlinear predictive controller for a distributed drive electric vehicle. First, nonlinear lateral dynamics of the vehicle are applied to develop the stability controller on low friction coefficient surfaces. Second, the requirement for suppressing the sideslip angle is integrated into the objective function to prevent the vehicle from destabilizing due to excessive sideslip angles. Finally, a fast solution algorithm is proposed by solving the transformed two-point boundary value problem, making it possible to apply nonlinear predictive controller to experimental road tests. The experiments with a production vehicle are conducted on the snow-covered dynamic roads of the DongFeng's winter test center. The test results on low friction coefficient roads show that the overall passing speed can be improved from 50-55 to 60-70 km/h with the proposed controller. |
| doi_str_mv | 10.1109/TCST.2020.3015832 |
| format | Article |
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To address these problems, this brief proposes a real-time nonlinear predictive controller for a distributed drive electric vehicle. First, nonlinear lateral dynamics of the vehicle are applied to develop the stability controller on low friction coefficient surfaces. Second, the requirement for suppressing the sideslip angle is integrated into the objective function to prevent the vehicle from destabilizing due to excessive sideslip angles. Finally, a fast solution algorithm is proposed by solving the transformed two-point boundary value problem, making it possible to apply nonlinear predictive controller to experimental road tests. The experiments with a production vehicle are conducted on the snow-covered dynamic roads of the DongFeng's winter test center. The test results on low friction coefficient roads show that the overall passing speed can be improved from 50-55 to 60-70 km/h with the proposed controller.</description><identifier>ISSN: 1063-6536</identifier><identifier>EISSN: 1558-0865</identifier><identifier>DOI: 10.1109/TCST.2020.3015832</identifier><identifier>CODEN: IETTE2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Boundary value problems ; Coefficient of friction ; Control stability ; Controllers ; Dynamic stability ; Electric vehicles ; Experimental verification ; Friction ; Lateral stability ; low friction coefficient ; Nonlinear control ; Nonlinear dynamics ; nonlinear model of predictive control (NMPC) ; Pontryagin’s minimum principle (PMP) ; Predictive control ; Real time ; Real-time systems ; Road tests ; Sideslip ; Snow cover ; Stability analysis ; Surface stability ; Tires ; Vehicle dynamics ; vehicle stability control ; Wheels</subject><ispartof>IEEE transactions on control systems technology, 2021-09, Vol.29 (5), p.2206-2213</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-c9c1ab53c718b1586bfca1096190948006eb056c1adfcffab7f294649fe432e03</citedby><cites>FETCH-LOGICAL-c293t-c9c1ab53c718b1586bfca1096190948006eb056c1adfcffab7f294649fe432e03</cites><orcidid>0000-0002-1724-8649 ; 0000-0003-2285-2469 ; 0000-0003-2729-2907 ; 0000-0002-9358-0264 ; 0000-0001-6718-8392 ; 0000-0002-9947-1034</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9199111$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9199111$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wang, Ping</creatorcontrib><creatorcontrib>Liu, Hanghang</creatorcontrib><creatorcontrib>Guo, Lulu</creatorcontrib><creatorcontrib>Zhang, Lin</creatorcontrib><creatorcontrib>Ding, Haitao</creatorcontrib><creatorcontrib>Chen, Hong</creatorcontrib><title>Design and Experimental Verification of Real-Time Nonlinear Predictive Controller for Improving the Stability of Production Vehicles</title><title>IEEE transactions on control systems technology</title><addtitle>TCST</addtitle><description>Vehicle stability control under extreme conditions is influenced by the coupled nonlinear characteristics of vehicle dynamics, corresponding safety constraints, and rapid response requirements. To address these problems, this brief proposes a real-time nonlinear predictive controller for a distributed drive electric vehicle. First, nonlinear lateral dynamics of the vehicle are applied to develop the stability controller on low friction coefficient surfaces. Second, the requirement for suppressing the sideslip angle is integrated into the objective function to prevent the vehicle from destabilizing due to excessive sideslip angles. Finally, a fast solution algorithm is proposed by solving the transformed two-point boundary value problem, making it possible to apply nonlinear predictive controller to experimental road tests. The experiments with a production vehicle are conducted on the snow-covered dynamic roads of the DongFeng's winter test center. The test results on low friction coefficient roads show that the overall passing speed can be improved from 50-55 to 60-70 km/h with the proposed controller.</description><subject>Algorithms</subject><subject>Boundary value problems</subject><subject>Coefficient of friction</subject><subject>Control stability</subject><subject>Controllers</subject><subject>Dynamic stability</subject><subject>Electric vehicles</subject><subject>Experimental verification</subject><subject>Friction</subject><subject>Lateral stability</subject><subject>low friction coefficient</subject><subject>Nonlinear control</subject><subject>Nonlinear dynamics</subject><subject>nonlinear model of predictive control (NMPC)</subject><subject>Pontryagin’s minimum principle (PMP)</subject><subject>Predictive control</subject><subject>Real time</subject><subject>Real-time systems</subject><subject>Road tests</subject><subject>Sideslip</subject><subject>Snow cover</subject><subject>Stability analysis</subject><subject>Surface stability</subject><subject>Tires</subject><subject>Vehicle dynamics</subject><subject>vehicle stability control</subject><subject>Wheels</subject><issn>1063-6536</issn><issn>1558-0865</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE9PAjEQxTdGExH9AMZLE8-L_bNbtkeDqCREiSDXTbdMoWRpsVuI3P3gdoV4mpfMmzczvyS5JbhHCBYPs8F01qOY4h7DJC8YPUs6JM-LFBc8P48ac5bynPHL5Kpp1hiTLKf9TvLzBI1ZWiTtAg2_t-DNBmyQNZpHqY2SwTiLnEYfIOt0FrvozdnaWJAeTTwsjApmD2jgbPCursEj7Twabbbe7Y1dorACNA2yMrUJhzZo4t1ip_5i57AyqobmOrnQsm7g5lS7yefzcDZ4TcfvL6PB4zhVVLCQKqGIrHKm-qSo4pO80krG5zkRWGQFxhwqnPNoWmiltaz6moqMZ0JDxihg1k3uj7nxuK8dNKFcu523cWVJI6uCZqzPooscXcq7pvGgy22kIv2hJLhsYZct7LKFXZ5gx5m744wBgH-_IEIQQtgvFIh9TQ</recordid><startdate>202109</startdate><enddate>202109</enddate><creator>Wang, Ping</creator><creator>Liu, Hanghang</creator><creator>Guo, Lulu</creator><creator>Zhang, Lin</creator><creator>Ding, Haitao</creator><creator>Chen, Hong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-1724-8649</orcidid><orcidid>https://orcid.org/0000-0003-2285-2469</orcidid><orcidid>https://orcid.org/0000-0003-2729-2907</orcidid><orcidid>https://orcid.org/0000-0002-9358-0264</orcidid><orcidid>https://orcid.org/0000-0001-6718-8392</orcidid><orcidid>https://orcid.org/0000-0002-9947-1034</orcidid></search><sort><creationdate>202109</creationdate><title>Design and Experimental Verification of Real-Time Nonlinear Predictive Controller for Improving the Stability of Production Vehicles</title><author>Wang, Ping ; Liu, Hanghang ; Guo, Lulu ; Zhang, Lin ; Ding, Haitao ; Chen, Hong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-c9c1ab53c718b1586bfca1096190948006eb056c1adfcffab7f294649fe432e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Boundary value problems</topic><topic>Coefficient of friction</topic><topic>Control stability</topic><topic>Controllers</topic><topic>Dynamic stability</topic><topic>Electric vehicles</topic><topic>Experimental verification</topic><topic>Friction</topic><topic>Lateral stability</topic><topic>low friction coefficient</topic><topic>Nonlinear control</topic><topic>Nonlinear dynamics</topic><topic>nonlinear model of predictive control (NMPC)</topic><topic>Pontryagin’s minimum principle (PMP)</topic><topic>Predictive control</topic><topic>Real time</topic><topic>Real-time systems</topic><topic>Road tests</topic><topic>Sideslip</topic><topic>Snow cover</topic><topic>Stability analysis</topic><topic>Surface stability</topic><topic>Tires</topic><topic>Vehicle dynamics</topic><topic>vehicle stability control</topic><topic>Wheels</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Ping</creatorcontrib><creatorcontrib>Liu, Hanghang</creatorcontrib><creatorcontrib>Guo, Lulu</creatorcontrib><creatorcontrib>Zhang, Lin</creatorcontrib><creatorcontrib>Ding, Haitao</creatorcontrib><creatorcontrib>Chen, Hong</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on control systems technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wang, Ping</au><au>Liu, Hanghang</au><au>Guo, Lulu</au><au>Zhang, Lin</au><au>Ding, Haitao</au><au>Chen, Hong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Design and Experimental Verification of Real-Time Nonlinear Predictive Controller for Improving the Stability of Production Vehicles</atitle><jtitle>IEEE transactions on control systems technology</jtitle><stitle>TCST</stitle><date>2021-09</date><risdate>2021</risdate><volume>29</volume><issue>5</issue><spage>2206</spage><epage>2213</epage><pages>2206-2213</pages><issn>1063-6536</issn><eissn>1558-0865</eissn><coden>IETTE2</coden><abstract>Vehicle stability control under extreme conditions is influenced by the coupled nonlinear characteristics of vehicle dynamics, corresponding safety constraints, and rapid response requirements. To address these problems, this brief proposes a real-time nonlinear predictive controller for a distributed drive electric vehicle. First, nonlinear lateral dynamics of the vehicle are applied to develop the stability controller on low friction coefficient surfaces. Second, the requirement for suppressing the sideslip angle is integrated into the objective function to prevent the vehicle from destabilizing due to excessive sideslip angles. Finally, a fast solution algorithm is proposed by solving the transformed two-point boundary value problem, making it possible to apply nonlinear predictive controller to experimental road tests. The experiments with a production vehicle are conducted on the snow-covered dynamic roads of the DongFeng's winter test center. The test results on low friction coefficient roads show that the overall passing speed can be improved from 50-55 to 60-70 km/h with the proposed controller.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TCST.2020.3015832</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-1724-8649</orcidid><orcidid>https://orcid.org/0000-0003-2285-2469</orcidid><orcidid>https://orcid.org/0000-0003-2729-2907</orcidid><orcidid>https://orcid.org/0000-0002-9358-0264</orcidid><orcidid>https://orcid.org/0000-0001-6718-8392</orcidid><orcidid>https://orcid.org/0000-0002-9947-1034</orcidid></addata></record> |
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| subjects | Algorithms Boundary value problems Coefficient of friction Control stability Controllers Dynamic stability Electric vehicles Experimental verification Friction Lateral stability low friction coefficient Nonlinear control Nonlinear dynamics nonlinear model of predictive control (NMPC) Pontryagin’s minimum principle (PMP) Predictive control Real time Real-time systems Road tests Sideslip Snow cover Stability analysis Surface stability Tires Vehicle dynamics vehicle stability control Wheels |
| title | Design and Experimental Verification of Real-Time Nonlinear Predictive Controller for Improving the Stability of Production Vehicles |
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