Optimum Design for the Magnification Mechanisms Employing Fuzzy Logic–ANFIS

Abstract

To achieve high work performance for compliant mechanisms of motion scope, continuous work condition, and high frequency, we propose a new hybrid algorithm that could be applied to multi-objective optimum design. In this investigation, we use the tools of finite element analysis (FEA) for a magnification mechanism to find out the effects of design variables on the magnification ratio of the mechanism and then select an optimal mechanism that could meet design requirements. A poly-algorithm including the Grey-Taguchi method, fuzzy logic system, and adaptive neuro-fuzzy inference system (ANFIS) algorithm, was utilized mainly in this study. The FEA outcomes indicated that design variables have significantly affected on magnification ratio of the mechanism and verified by analysis of variance and analysis of the signal to noise of grey relational grade. The results are also predicted by employing the tool of ANFIS in MATLAB. In conclusion, the optimal findings obtained: Its magnification is larger than 40 times in comparison with the initial design, the maximum principal stress is 127.89 MPa, and the first modal shape frequency obtained 397.45 Hz. Moreover, we found that the outcomes obtained deviation error compared with predicted results of displacement, stress, and frequency are 8.76%, 3.6%, and 6.92%, respectively.

Design optimization of a novel symmetrical differential lever displacement magnification compliant mechanism

“…The negative distance (PD) values were obtained by substituting the displacement and stress values in Table 2 into Eqs. (28)(29). SoPi values were obtained by substituting the positive distance of displacement and stress value into Eq.…”

“…The results of this novel method were verified through FEA and experimentation. The optimization of the displacement amplification ratio of magnification mechanism [29] was also obtained using a fuzzy logic-adative neuro fuzzy inference system. A type of symmetrical differential lever displacement amplification mechanism [30] was then designed based on the finite element analysis and the results of simulation in ANSYS.…”

Optimization of Maintenance Schedule for Containerships Sailing in the Adriatic Sea

“…This would allow the development of a comprehen sive model for cleaning scheduling, which could be very beneficial for shipowners and ship operators. Within the literature, there are numerous optimization methods that ar based on artificial intelligence [48], fuzzy logic, adaptive neuro-fuzzy inference system [49], and others that are especially useful within multi-objective optimization problems For example, Hou et al [50] used the Kriging-based response surface method and multi objective optimization algorithm for hull shape optimization of a small underwater vehi cle. The model proposed in this paper is a single objective optimization problem and, a such, does not require the utilisation of the previously mentioned complex algorithms.…”

Neuro-Fuzzy Based High-Voltage DC Model to Optimize Frequency Stability of an Offshore Wind Farm

“…The proposed control strategy offers several advantages over existing methods in terms of frequency stability, including the use of a hybrid LCVSV-HVDC system, improved integration of offshore wind farms, and an ANFIS-based controlling technique [51]. Moreover, the proposed control strategy is flexible and adaptable, and it caters to the ever-changing dynamics of both wind speed and power demand.…”