稳健性(进化)
控制理论(社会学)
参数统计
振动
欠驱动
计算机科学
残余物
数学优化
工程类
数学
人工智能
算法
控制(管理)
物理
生物化学
化学
统计
量子力学
基因
作者
Paolo Boscariol,Dario Richiedei,Alberto Trevisani
标识
DOI:10.1177/10775463241259296
摘要
Motion planning is an effective tool for the suppression of residual oscillation in underactuated mechanical systems, and in particular, model-based method can be used to virtually eliminate any unwanted oscillation after the completion of a motion task. Here, a novel motion planning method, aimed at maximizing robustness to model uncertainties and based on a direct formulation, is proposed and tested. The choice of a direct formulation is aimed at overcoming the numerical problems often encountered when dealing with indirect trajectory planning methods, including the limited robustness to any model-plant mismatch. The proposed direct method is based on three different motion profiles, and is tested for the rest-to-rest motion of a slender beam, with and without parametric robustness constraints, but the same framework can be adapted to countless other situations and formulations. The experimental results showcase good accuracy and a sensible improvement in mitigating the effects of unmodeled perturbations on the system sported by the proposed robustified method over its non-robust counterpart. Experimental results show also the outcome is very similar to the one resulting from a more numerically challenging solution formulated as an indirect problem by means of a two-point boundary value problem.
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