Abstract

Compliant mechanisms are promising candidates in precision engineering, soft robotics, space, and bioengineering due to their advantages of free friction, free lubricant, no backlash, monolithic structure, and minimal assembly. However, designing and analyzing of compliant mechanisms are facing the high complexity due to a coupling of kinematic and mechanical behavior in comparison to rigid-body mechanisms. Especially, considering a multi-objective optimization design for compliant mechanisms, the problem is more complicated. Thus, this paper presents a new efficient hybrid methodology for solving the multi-objective optimization design. A hybridization is developed through a combination of finite element method, statistical technique, desirability function approach, fuzzy logic system, adaptive neuro-fuzzy inference system (ANFIS), and Lightning attachment procedure optimization (LAPO). A bistable compliant mechanism is investigated as an application example of the proposed method. First, design variables of the mechanism are determined, and then central composite design is employed to construct a numerically experimental matrix. Though using analysis of variance and Taguchi approach, the design variables are refined to make new populations. Subsequently, desirability values of two performances of the mechanism are computed, and the results are transferred into the fuzzy logic system. The output of fuzzy logic system is considered as single combined objective function. By developing the ANFIS model, the relation between the refined design variables and the output of fuzzy logic system is established. Finally, LAPO algorithm is adopted for solving the multi-objective optimization problem for the mechanism. Three numerical examples are investigated to validate the performance efficiency of the proposed method. The results demonstrate that the proposed method is more efficient than Taguchi-based fuzzy logic. Besides, through Wilcoxon signed rank test and Friedman test, it reveals that the performances of proposed approach are superior to those of the Jaya algorithm and TLBO algorithm. The results of this article can be extended for other complex compliant mechanisms as well as optimization problems with multiple objective functions and more complex constraints.

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