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En el instante 11 de octubre de 2025, 1:23:29 UTC,
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Añadido recurso Mechatronic design of a planar robot using multiobjective optimization a Mechatronic design of a planar robot using multiobjective optimization
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2 | "author": "AR Suarez, SI Valdez, EE Hernandez", | 2 | "author": "AR Suarez, SI Valdez, EE Hernandez", | ||
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42 | ign-of-a-planar-robot-using-multiobjective-optimization-4bc046e7a957", | 42 | ign-of-a-planar-robot-using-multiobjective-optimization-4bc046e7a957", | ||
43 | "notes": "The concurrent design optimization of robots refers to the | 43 | "notes": "The concurrent design optimization of robots refers to the | ||
44 | problem of optimizing parameters that affects different kinds of | 44 | problem of optimizing parameters that affects different kinds of | ||
45 | features at the same time. For instance, this work presents a study | 45 | features at the same time. For instance, this work presents a study | ||
46 | case for the concurrent design optimization of the structure and | 46 | case for the concurrent design optimization of the structure and | ||
47 | control of a parallelogram mechanism. The main contribution of this | 47 | control of a parallelogram mechanism. The main contribution of this | ||
48 | work is the definition of an integrated optimization model that | 48 | work is the definition of an integrated optimization model that | ||
49 | considers two conflicting objectives, defined as the energy and error | 49 | considers two conflicting objectives, defined as the energy and error | ||
50 | during a trajectory tracking. In addition, the optimization model | 50 | during a trajectory tracking. In addition, the optimization model | ||
51 | considers an error constraint, with the purpose of automatically | 51 | considers an error constraint, with the purpose of automatically | ||
52 | discarding designs that can not closely follow the trajectory, and the | 52 | discarding designs that can not closely follow the trajectory, and the | ||
53 | simulation considers a saturation constraint that avoids to deliver | 53 | simulation considers a saturation constraint that avoids to deliver | ||
54 | torques above a threshold. The multi-objective optimization problem is | 54 | torques above a threshold. The multi-objective optimization problem is | ||
55 | solved using the Multi-objective Evolutionary Algorithm Based on | 55 | solved using the Multi-objective Evolutionary Algorithm Based on | ||
56 | Decomposition (MOEA/D), the resulting solutions, named Pareto set, are | 56 | Decomposition (MOEA/D), the resulting solutions, named Pareto set, are | ||
57 | delivered to a final decision maker, to select the adequate design | 57 | delivered to a final decision maker, to select the adequate design | ||
58 | among those with the best compromise between minimum tracking error | 58 | among those with the best compromise between minimum tracking error | ||
59 | and energy consumption. A design is a set of lengths and control | 59 | and energy consumption. A design is a set of lengths and control | ||
60 | gains, hence, notice that the control gains are optimized for the | 60 | gains, hence, notice that the control gains are optimized for the | ||
61 | corresponding geometry.", | 61 | corresponding geometry.", | ||
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169 | "title": "Mechatronic design of a planar robot using multiobjective | 211 | "title": "Mechatronic design of a planar robot using multiobjective | ||
170 | optimization", | 212 | optimization", | ||
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