Constraint-Handling Techniques for the Concurrent Design of a Five-Bar Parallel Robot

Cervantes-Culebro, Héctor; Cruz-Villar, Carlos A.; Penaloza, Maria-Guadalupe Martinez; Mezura-Montes, Efrén

doi:10.1109/access.2017.2764883

Cited by 11 publications

(7 citation statements)

References 21 publications

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“…The SPBR structural design is also constrained by the upper and lower bounds of the geometric design variables through (30) and (31), where the maximum and minimum values of each geometric structural variable are established in Table 2. In the case of semi-passive control design variables, the torque magnitudes are limited through the expressions (33) and (34). The upper and lower torque values are p τ,max = 1.5Nm • 1 and p τ,min = 0, where 1 ∈ R k sp s and 0 ∈ R k sp s are vectors with elements set as one and zero, respectively.…”

Section: Constraintsmentioning

confidence: 99%

“…Due to gradient-based optimization techniques cannot efficiently handle system discontinuities, the meta-heuristic optimization method is implemented. Based on the successful use of the DE algorithm in solving integrated design problems of mechatronic systems such as in pinion-rack continuously variable transmissions [28], in five-bar parallel robots [32,33] and in digital displacement machine [34], the variant DE/rand/1/bin [35] with a constraint handling mechanism [36] is applied in the proposal with the aim of guiding the solution search towards the feasible design region. Furthermore, because the material assignment of structural elements is related to a finite set of available materials, a discrete variable handling is incorporated into the DE algorithm [37].…”

Section: Introductionmentioning

confidence: 99%

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Integrated Structure-Control Design of a Bipedal Robot Based on Passive Dynamic Walking

Martinez-Castelan

Villarreal-Cervantes

2021

Mathematics

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The design of bipedal robots is generally fulfilled through considering a sequential design approach, where a synergistic relationship between its structure and control features is not promoted. Hence, a novel integrated structure-control design approach is proposed to simultaneously obtain the optimal structural description, the torque magnitudes, and the on/off time intervals for the control signal input of a semi-passive bipedal robot. The proposed approach takes advantage of the natural dynamics of the system and the control signal activation/deactivation for generating stable gait cycles with minimum energy consumption. Consequently, the passive features of the semi-passive bipedal robot are included in the integrated structure-control design process through evaluating the system behavior along consecutive passive and semi-passive walking stages. Then, the proposed design approach is formulated as a nonlinear discontinuous dynamic optimization problem, where the solution search is carried out using the differential evolution algorithm due to the discontinuities of the semi-passive bipedal robot dynamics. The results of the proposal are compared with those obtained by a sequential design process. The integrated structure-control design achieves a reduction of 63.55% in the value of the performance function related to the synergy between the walking capability and energetic efficiency, with a reduction in the activation of the control and its magnitude of 95.41%.

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Section: Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated Structure-Control Design of a Bipedal Robot Based on Passive Dynamic Walking

Martinez-Castelan

Villarreal-Cervantes

2021

Mathematics

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“…We observed in the literature that metaheuristic algorithms in their original versions were proposed to solve unconstrained optimization problems. Thus, it is important to find the most promising techniques for including real-word constraints [37][38][39]. Currently, for the solution of constrained optimization problems, CHTs have been proposed.…”

Section: Studymentioning

confidence: 99%

Empirical Study of Constraint-Handling Techniques in the Optimal Synthesis of Mechanisms for Rehabilitation

2021

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Currently, rehabilitation systems with closed kinematic chain mechanisms are low-cost alternatives for treatment and health care. In designing these systems, the dimensional synthesis is commonly stated as a constrained optimization problem to achieve repetitive rehabilitation movements, and metaheuristic algorithms for constrained problems are promising methods for searching solutions in the complex search space. The Constraint Handling Techniques (CHTs) in metaheuristic algorithms have different capacities to explore and exploit the search space. However, the study of the relationship in the CHT performance of the mechanism dimensional synthesis for rehabilitation systems has not been addressed, resulting in an important gap in the literature of such problems. In this paper, we present a comparative empirical study to investigate the influence of four CHTs (penalty function, feasibility rules, stochastic-ranking, and ϵ-constraint) on the performance of ten representative algorithms that have been reported in the literature for solving mechanism synthesis for rehabilitation (four-bar linkage, eight-bar linkage, and cam-linkage mechanisms). The study involves analysis of the overall performance, six performance metrics, and evaluation of the obtained mechanism. This identified that feasibility rules usually led to efficient optimization for most analyzed algorithms and presented more consistency of the obtained results in these kinds of problems.

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“…Ali et al [45] integrated stochastic ranking with an evolutionary algorithm to maintain a balance between penalty and objective functions, which can only address constrained continuous problems with a single objective. Besides, to minimize energy consumption, Hector et al [46] used alternately stochastic ranking, feasibility rules, and 8-constrained methods to analyze the design changes, and validated that stochastic ranking method always obtains better solutions in all proposed torque limits.…”

Section: Introductionmentioning

confidence: 99%

Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems

Wang

Xiong

et al. 2021

Complex Intell. Syst.

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Surrogate-assisted optimization has attracted much attention due to its superiority in solving expensive optimization problems. However, relatively little work has been dedicated to addressing expensive constrained multi-objective discrete optimization problems although there are many such problems in the real world. Hence, a surrogate-assisted evolutionary algorithm is proposed in this paper for this kind of problem. Specifically, random forest models are embedded in the framework of the evolutionary algorithm as surrogates to improve approximate accuracy for discrete optimization problems. To enhance the optimization efficiency, an improved stochastic ranking strategy based on the fitness mechanism and adaptive probability operator is presented, which also takes into account both convergence and diversity to advance the quality of candidate solutions. To validate the proposed algorithm, it is comprehensively compared with several well-known optimization algorithms on several benchmark problems. Numerical experiments are demonstrated that the proposed algorithm is very promising for the expensive constrained multi-objective discrete optimization problems.

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Constraint-Handling Techniques for the Concurrent Design of a Five-Bar Parallel Robot

Cited by 11 publications

References 21 publications

Integrated Structure-Control Design of a Bipedal Robot Based on Passive Dynamic Walking

Integrated Structure-Control Design of a Bipedal Robot Based on Passive Dynamic Walking

Empirical Study of Constraint-Handling Techniques in the Optimal Synthesis of Mechanisms for Rehabilitation

Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems

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