Optimal Design of a Compliant Microgripper for Assemble System of Cell Phone Vibration Motor Using a Hybrid Approach of ANFIS and Jaya

Ho, Nhat; Dao, Thanh-Phong; Le, Hieu Giang; Chau, Ngoc Le

doi:10.1007/s13369-018-3445-2

Cited by 26 publications

(13 citation statements)

References 43 publications

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“…For the proposed LCM, the sensitivity analysis was mainly focused on three characteristics. Generally, there were many methods that can be applied for calculating the sensitivity such as Nelson method, modal method, matrix perturbation method, differential method, RSM, or statistical analysis [31,32]. For example, the direct differential method takes more time for analysis because it needs to construct physical models.…”

Section: Optimal Results By Using Phase 3 and Begining Frommentioning

confidence: 99%

An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester

Chau

Dao

Nguyễn

2018

Mathematical Problems in Engineering

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This paper proposes a new evolutionary multiobjective optimization technique for a linear compliant mechanism of nanoindentation tester. The mechanism design is inspired by the elastic deformation of flexure hinge. To improve overall static performances, a multiobjective optimization design was carried out. An efficient hybrid optimization approach of central composite design (CDD), finite element method (FEM), artificial neural network (ANN), and multiobjective genetic algorithm (MOGA) is developed to solve the optimization problem. In this procedure, the CDD is used to lay out the experimental data. The FEM is developed to retrieve the quality performances. And then, the ANN is developed as black box to call the pseudo-objective functions. Unlike previous studies on multiobjective evolutionary algorithms, most of which generating only one Pareto-optimal solution, this proposed approach can generate more than three Pareto-optimal solutions. Based on the user’s real-work problem, one of the best optimal solutions is chosen. The results showed that the optimal results were found at the displacement of 330.68 μm, stress of 140.65 MPa, and safety factor of 3.6. The statistical analysis is conducted to investigate the behavior of the MOGA. The sensitivity analysis was carried out to determine the significant contribution of each factor. The results revealed that the lengths and thickness almost significantly affect both responses. It confirms that the proposed hybrid optimization approach gains high robustness and effectiveness with flexible decision maker rules to solve complex optimization engineering problems.

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Section: Optimal Results By Using Phase 3 and Begining Frommentioning

confidence: 99%

An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester

Chau

Dao

Nguyễn

2018

Mathematical Problems in Engineering

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“…Besides, resulting stress should be also under the yield strength of the proposed material so that the CRJ can operate without plastic failures. Because the CRJ is constructed based on the concept of CMs [19][20][21][22], a field of non-traditional mechanical engineering, the quality characteristics of joint greatly depend on the thickness and length of the leaf springs. If the twisted step of leaf springs is constant, the length of leaf spring depends on the diameter of the CRJ.…”

Section: Proposed Hybrid Methodologymentioning

confidence: 99%

“…Therefore, the present study proposes a multi-objective optimization of the CRJ. The CRJ is constructed based on a compliant mechanism (CM) that is an outperformed mechanism compared to conventional mechanisms due to its advantages, such as miniature size, being lightweight, increased accuracy, energy storage capability, and decreased vibrations [19][20][21][22]. The qualities of CRJ include a large rotational motion to be suitable for different people, being lightweight to be easily integrated into the upper limb, and minimal stress.…”

Section: Introductionmentioning

confidence: 99%

Efficient Hybrid Method of FEA‐Based RSM and PSO Algorithm for Multi‐Objective Optimization Design for a Compliant Rotary Joint for Upper Limb Assistive Device

Chau

Dao

et al. 2019

Mathematical Problems in Engineering

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This paper proposes an efficient hybrid methodology for multi-objective optimization design of a compliant rotary joint (CRJ). A combination of the Taguchi method (TM), finite element analysis (FEA), the response surface method (RSM), and particle swarm optimization (PSO) algorithm is developed to solving the optimization problem. Firstly, the TM is applied to determine the number of numerical experiments. And then, 3D models of the CRJ is built for FEA simulation, and mathematical models are formed using the RSM. Subsequently, the suitability of the regression equation is assessed. At the same time, the calculation of weight factors is identified based on the series of statistical equations. Based on the well-established equations, a minimum mass and a maximum rotational angle are simultaneously optimized through the PSO algorithm. Analysis of variance is used to analyze the contribution of design variables. The behavior of the proposed method is compared to the adaptive elitist differential evolution and cuckoo search algorithm through the Wilcoxon signed rank test and Friedman test. The results determined the weight factors of the mass and rotational angle are about 0.4983 and 0.5017, respectively. The results found that the optimum the mass and rotational angle are 0.0368 grams and 59.1928 degrees, respectively. It revealed that the maximum stress of 335 MPa can guarantee a long working time. The results showed that the proposed hybrid method outperforms compared to other evolutionary algorithms. The predicted results are close to the validation results. The proposed method is useful for related engineering fields.

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“…Flexure-guide based piezo-actuated positioning stage with all-ceramic insulation offers high travel accuracy, rapid response, high load capacity and longer lifetime than conventional polymer-insulated actuators. Flexure-guide based positioning stages have been widely used in different precision engineering applications from one degree of freedom to six degrees of freedom [40]- [42]. The travel range of the considered piezoelectric actuator is 35 µm with the resolution of 0.2 nm and maximum load capacity of 30 N. The specifications of the considered piezoactuated micropositioning stage are listed in Table 1.…”

Section: Description Of Piezo-actuated Micropositioning Stagementioning

confidence: 99%

Robust μ-Synthesis With Dahl Model Based Feedforward Compensator Design for Piezo-Actuated Micropositioning Stage

Ahmad

Ali

2020

IEEE Access

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In this paper, a combined feedback-feedforward control design scheme is presented to enhance the tracking performance of a piezo-actuated micropositioning stage by compensating the nonlinear hysteretic behavior of the piezoelectric actuator and model uncertainties of the system. Detailed investigation of the presented control scheme is performed not only in simulation by analyzing the robust stability and robust performance but also in real-time with motion trajectories of multiple frequencies. To design the presented control scheme, first of all, the dynamic model of the system is identified from the real-time experimental data by using the recursive least squares parameter adaptation algorithm. Then, Dahl hysteresis model is considered to represent the nonlinear hysteretic behavior of the piezoelectric actuator. To deal with this hysteresis nonlinearity, Dahl feedforward compensator is designed without involving inverse model calculations to avoid any computational complexity. This feedforward compensator is then combined with µ-synthesis robust feedback controller which is designed in the presence of model uncertainties of the system. The presented control scheme ensures the boundedness of the closed-loop signals and the desired tracking performance of the considered micropositioning stage. Finally, experimental tests are conducted with motion trajectories of multiple frequencies for the validation of the control scheme. An average improvement of 95% in compensating the hysteresis nonlinearity and 80% in reducing the tracking error is achieved which demonstrates the efficacy of the presented control scheme. INDEX TERMS Dahl feedforward compensator, hysteresis nonlinearity, micropositioning, model uncertainties, piezoelectric actuator, µ-synthesis robust feedback controller.

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Optimal Design of a Compliant Microgripper for Assemble System of Cell Phone Vibration Motor Using a Hybrid Approach of ANFIS and Jaya

Cited by 26 publications

References 43 publications

An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester

An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester

Efficient Hybrid Method of FEA‐Based RSM and PSO Algorithm for Multi‐Objective Optimization Design for a Compliant Rotary Joint for Upper Limb Assistive Device

Robust μ-Synthesis With Dahl Model Based Feedforward Compensator Design for Piezo-Actuated Micropositioning Stage

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