Adaptive predictive functional control of a class of nonlinear systems
This paper describes the use of pseudo-partial derivative (PPD) to dynamically linearize a nonlinear system, and aggregation is applied to the predicted PPD, resulting in a model-free adaptive predictive control algorithm for a nonlinear system. The algorithm design is only based on the PPD derived...
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Veröffentlicht in: | ISA transactions 2006-04, Vol.45 (2), p.175-183 |
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description | This paper describes the use of pseudo-partial derivative (PPD) to dynamically linearize a nonlinear system, and aggregation is applied to the predicted PPD, resulting in a model-free adaptive predictive control algorithm for a nonlinear system. The algorithm design is only based on the PPD derived online from the input/output data of the controlled process, however it does provide bounded input/output sequence and setpoint tracking without steady-state error. A detailed discussion on parameter selection is also provided. To show the capability of the algorithm, simulations of a time-delay plant and a pH neutralization process show that the proposed method is effective for system parameter perturbation and external disturbance rejection. |
doi_str_mv | 10.1016/S0019-0578(07)60188-8 |
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The algorithm design is only based on the PPD derived online from the input/output data of the controlled process, however it does provide bounded input/output sequence and setpoint tracking without steady-state error. A detailed discussion on parameter selection is also provided. To show the capability of the algorithm, simulations of a time-delay plant and a pH neutralization process show that the proposed method is effective for system parameter perturbation and external disturbance rejection.</description><identifier>ISSN: 0019-0578</identifier><identifier>EISSN: 1879-2022</identifier><identifier>DOI: 10.1016/S0019-0578(07)60188-8</identifier><identifier>PMID: 16649564</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Adaptative systems ; Aggregation ; Applied sciences ; Base functions ; Computer science; control theory; systems ; Control theory. 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The algorithm design is only based on the PPD derived online from the input/output data of the controlled process, however it does provide bounded input/output sequence and setpoint tracking without steady-state error. A detailed discussion on parameter selection is also provided. To show the capability of the algorithm, simulations of a time-delay plant and a pH neutralization process show that the proposed method is effective for system parameter perturbation and external disturbance rejection.</description><subject>Adaptative systems</subject><subject>Aggregation</subject><subject>Applied sciences</subject><subject>Base functions</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Dynamic linearization</subject><subject>Exact sciences and technology</subject><subject>Nonlinear system</subject><subject>Predictive functional control</subject><issn>0019-0578</issn><issn>1879-2022</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNqFkMtKAzEUhoMoWquPoMxG0cVoMmluK5HiDQou1HVIMycQmSY1mRZ8e9N20KWr8y--c_sQOiP4hmDCb98wJqrGTMgrLK45JlLWcg-NiBSqbnDT7KPRL3KEjnP-xBg3TMlDdEQ4nyjGJyP0eN-aZe_XUC0TtN5uo1uFEmIwXWVj6FPsqugqU9nO5LyJIYbOBzCpyt-5h0U-QQfOdBlOhzpGH48P79Pnevb69DK9n9WWKtrXLQNOORBmGVfQKuLwRMGczkEZShorWmiss45JSrFgrSl_Ucon0jUcGBg6Rpe7ucsUv1aQe73w2ULXmQBxlTUXinApeQHZDrQp5pzA6WXyC5O-NcF6I1BvBeqNHY2F3grUsvSdDwtW8wW0f12DsQJcDIDJ1nQumWB9_uMEL7crUbi7HQdFx9pD0tl6CLZITmB73Ub_zyk_t2aNSg</recordid><startdate>20060401</startdate><enddate>20060401</enddate><creator>Zhang, Bin</creator><creator>Zhang, Weidong</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20060401</creationdate><title>Adaptive predictive functional control of a class of nonlinear systems</title><author>Zhang, Bin ; Zhang, Weidong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c393t-d5e636e15c569ed91f049eb3be9a312c7de2cfcf5833075da60133648f26e5ea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Adaptative systems</topic><topic>Aggregation</topic><topic>Applied sciences</topic><topic>Base functions</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>Dynamic linearization</topic><topic>Exact sciences and technology</topic><topic>Nonlinear system</topic><topic>Predictive functional control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Bin</creatorcontrib><creatorcontrib>Zhang, Weidong</creatorcontrib><collection>Pascal-Francis</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>ISA transactions</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Bin</au><au>Zhang, Weidong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive predictive functional control of a class of nonlinear systems</atitle><jtitle>ISA transactions</jtitle><addtitle>ISA Trans</addtitle><date>2006-04-01</date><risdate>2006</risdate><volume>45</volume><issue>2</issue><spage>175</spage><epage>183</epage><pages>175-183</pages><issn>0019-0578</issn><eissn>1879-2022</eissn><abstract>This paper describes the use of pseudo-partial derivative (PPD) to dynamically linearize a nonlinear system, and aggregation is applied to the predicted PPD, resulting in a model-free adaptive predictive control algorithm for a nonlinear system. The algorithm design is only based on the PPD derived online from the input/output data of the controlled process, however it does provide bounded input/output sequence and setpoint tracking without steady-state error. A detailed discussion on parameter selection is also provided. To show the capability of the algorithm, simulations of a time-delay plant and a pH neutralization process show that the proposed method is effective for system parameter perturbation and external disturbance rejection.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>16649564</pmid><doi>10.1016/S0019-0578(07)60188-8</doi><tpages>9</tpages></addata></record> |
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subjects | Adaptative systems Aggregation Applied sciences Base functions Computer science control theory systems Control theory. Systems Dynamic linearization Exact sciences and technology Nonlinear system Predictive functional control |
title | Adaptive predictive functional control of a class of nonlinear systems |
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