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• W2053526927 abstract "Model-based trajectory planning algorithms are capable of providing a high level of performance. However, they are often lacking in robustness, which severely limits their field of application. In this paper the method of parametric desensitization is applied to nonlinear models, providing a feasible solution to the problem of robust model-based trajectory planning for nonlinear plants with parametric uncertainties. By using an indirect variational solution method, the necessary optimality conditions deriving from Pontryagin's minimum principle are imposed, and lead to a differential two-point boundary value problem; numerical solution of the latter is accomplished by means of collocation techniques. The method is applied to two test cases: a nonlinear spring–mass system and a flexible link manipulator with Coulombian friction. Results show that the technique developed in this paper can significantly improve the robustness of the resulting trajectory to parametric model mismatches in comparison with the conventional method." @default.
• W2053526927 created "2016-06-24" @default.
• W2053526927 creator A5029638799 @default.
• W2053526927 creator A5048282687 @default.
• W2053526927 date "2016-08-09" @default.
• W2053526927 modified "2023-09-27" @default.
• W2053526927 title "Robust model-based trajectory planning for nonlinear systems" @default.
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• W2053526927 doi "https://doi.org/10.1177/1077546314566834" @default.
• W2053526927 hasPublicationYear "2016" @default.
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