2020
DOI: 10.1016/j.jfranklin.2020.04.019
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Stability and stabilization for LPV systems based on Lyapunov functions with non-monotonic terms

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Cited by 32 publications
(14 citation statements)
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“…F I G U R E 1 Domain of attraction estimation for the exact discrete-time system and state trajectories of the sampled-data system (27) in feedback with (8) designed with Lemma 3. Each trajectory is generated for a different value of -Example 1…”
Section: Illustrative Examplesmentioning
confidence: 99%
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“…F I G U R E 1 Domain of attraction estimation for the exact discrete-time system and state trajectories of the sampled-data system (27) in feedback with (8) designed with Lemma 3. Each trajectory is generated for a different value of -Example 1…”
Section: Illustrative Examplesmentioning
confidence: 99%
“…As illustrated in Figure 3, as increases, the performance index log det (Q) related to the volume of the guaranteed domain of attraction estimation decreases, which indicates a commitment between sampling time and guaranteed performance. F I G U R E 2 Domain of attraction estimation for the exact discrete-time model and state trajectories of the sampled-data system (27) in feedback with (8) designed with Lemma 3. Each trajectory is generated for a different value of .…”
Section: Examplementioning
confidence: 99%
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“…In the case of LPV systems, the non-linearity is embedded in the time-varying parameters that depend on some endogenous signals [14][15][16]. Often, uncertain LTI systems can be seen as a particular case of LPV systems.…”
Section: Introductionmentioning
confidence: 99%
“…Considering time‐varying parameters and system constraints can lead to conservative design results. However, it is possible to reduce the conservativeness by selecting nonquadratic Lyapunov functions, such as parameter‐dependent Lyapunov functions, to perform stability analysis and control synthesis 14‐18 . Alternatively, nonlinear controllers can be used instead of classical linear approaches.…”
Section: Introductionmentioning
confidence: 99%