Data-Based Control of Feedback Linearizable Systems
We present an extension of Willems' Fundamental Lemma to the class of multi-input multi-output discrete-time feedback linearizable nonlinear systems, thus providing a data-based representation of their input-output trajectories. Two sources of uncertainty are considered. First, the unknown line...
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| Veröffentlicht in: | IEEE transactions on automatic control 2023-11, Vol.68 (11), p.1-8 |
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| container_title | IEEE transactions on automatic control |
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| creator | Alsalti, Mohammad Lopez, Victor G. Berberich, Julian Allgower, Frank Muller, Matthias A. |
| description | We present an extension of Willems' Fundamental Lemma to the class of multi-input multi-output discrete-time feedback linearizable nonlinear systems, thus providing a data-based representation of their input-output trajectories. Two sources of uncertainty are considered. First, the unknown linearizing input is inexactly approximated by a set of basis functions. Second, the measured output data is contaminated by additive noise. Further, we propose an approach to approximate the solution of the data-based simulation and output matching problems, and show that the difference from the true solution is bounded. Finally, the results are illustrated on an example of a fully-actuated double inverted pendulum. |
| doi_str_mv | 10.1109/TAC.2023.3249289 |
| format | Article |
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Finally, the results are illustrated on an example of a fully-actuated double inverted pendulum.</description><subject>Approximation error</subject><subject>Basis functions</subject><subject>Data models</subject><subject>Feedback</subject><subject>Mathematical models</subject><subject>Noise measurement</subject><subject>Nonlinear systems</subject><subject>Trajectory</subject><issn>0018-9286</issn><issn>1558-2523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkDFPwzAQRi0EEqGwMzBEYk6x7-zEHkuggFSJgTJbTnyRUtKm2OlQfn1TtQPT6Tu97056jN0LPhWCm6flrJwCB5wiSAPaXLBEKKUzUICXLOFc6Gzc59fsJsbVGHMpRcLwxQ0ue3aRfFr2myH0Xdo36ZzIV67-SRfthlxo_1zVUfq1jwOt4y27alwX6e48J-x7_ros37PF59tHOVtkNRgYMqyrmmtwIMmgAp8Lj9wVQpLySFrUWIHMRa59zqU0SqCsoOAGnfRN03icsMfT3W3of3cUB7vqd2EzvrSgNagCCiNHip-oOvQxBmrsNrRrF_ZWcHtUY0c19qjGntWMlYdTpSWifzhXUkCBBx0wXQM</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>Alsalti, Mohammad</creator><creator>Lopez, Victor G.</creator><creator>Berberich, Julian</creator><creator>Allgower, Frank</creator><creator>Muller, Matthias A.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| ispartof | IEEE transactions on automatic control, 2023-11, Vol.68 (11), p.1-8 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Approximation error Basis functions Data models Feedback Mathematical models Noise measurement Nonlinear systems Trajectory |
| title | Data-Based Control of Feedback Linearizable Systems |
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