Yiqing Li

Bio: Yiqing Li is an academic researcher. The author has contributed to research in topics: Inertia & Physics. The author has an hindex of 3, co-authored 3 publications receiving 222 citations.

Development and experiment evaluation of a compact inchworm piezoelectric actuator using three-jaw type clamping mechanism

Abstract: A compact inchworm piezoelectric actuator using three-jaw type clamping mechanism is developed in this study. Different from the previous inchworm piezoelectric actuators constructed with guiding structures, the proposed actuator can drive an output shaft to realize linear motion without other auxiliary structures based on the automatic centering and guidance functions of the designed three-jaw type clamping mechanism, and a compact structure is obtained. The configuration of the actuator is presented to describe the operating principle in detail. Then the structures of the clamping and actuating units are designed by the assistance of finite element simulations. A prototype is fabricated and a compact structure is achieved with outer diameter of 34 mm and length of 40 mm. The experiments are performed to investigate the characteristics, a maximum speed of 155.5 μm s−1 and a thrust force of 12.3 N are achieved. The experimental results confirm that the proposed inchworm actuator can achieve a compact structure by adopting the designed three-jaw type clamping mechanisms, it has great potential in integration with precision equipment, which is conductive to apply in the fields of biological manipulation robots and aerospace devices.

Modeling and experimental evaluation of dynamic behavior of a soft bending actuator with symmetrical fluidic chambers

Abstract: Shear deformation and nonlinearity are the two main variables that influence the bending behavior of soft actuators with thick cross-sections. However, in most dynamic studies of these actuators, either one such variable is taken into consideration or both are disregarded, resulting in substantial inaccuracies in predicting their dynamic responses. In this work, we present an analytical dynamic model based on Euler–Lagrange dynamics, to predict the bending behavior of a soft pneumatic actuator with symmetrical fluidic chambers, which can capture the shear deformation of the actuator while preserving its nonlinear characteristics. Inspired by the finite element method, we divided the actuator into several regions and calculated the strain potential energy of each region separately. The coupling between different regions was described as geometric constraints based on the constant curvature (CC) model. As the inertia term of the dynamic model, the actuator’s kinetic energy was evaluated under an assumption that the actuator’s mass distributes along the center line of the neutral layer. These efforts allowed the model to preserve the nonlinearity of the deformation while ensuring its simplicity. By looking for the minimum value of the stress potential energy, the shear deformation of the actuator was assessed. Experiments were carried out to determine the actuator’s damping properties, investigate the influence of the gas line on the actuator’s dynamic behavior, and validate the model at fluidic pressure with different frequencies. The dynamic model’s predictions for transient and steady stages were found to be in good agreement with experimental data. The model’s application to other soft actuators with a similar structure was discussed at the end.

Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection

Abstract: This research’s genesis is in two aspects: first, a guaranteed solution for mitigating the grey wolf optimizer’s (GWO) defect and deficiencies. Second, we provide new open-minding insights and deep views about metaheuristic algorithms. The population-based GWO has been recognized as a popular option for realizing optimal solutions. Despite the popularity, the GWO has structural defects and uncertain performance and has certain limitations when dealing with complex problems such as multimodality and hybrid functions. This paper tries to overhaul the shortcomings of the original process and develops a GWO variant enhanced with a covariance matrix adaptation evolution strategy (CMAES), levy flight mechanism, and orthogonal learning (OL) strategy named GWOCMALOL. The algorithm uses the levy flight mechanism, orthogonal learning strategy, and CMAES to bring more effective exploratory inclinations. We conduct numerical experiments based on various functions in IEEE CEC2014. It is also compared with 10 other algorithms with competitive performances, 7 improved GWO variants, and 11 advanced algorithms. Moreover, for more systematic data analysis, Wilcoxon signed-rank test is used to evaluate the results further. Experimental results show that the GWOCMALOL algorithm is superior to other algorithms in terms of convergence speed and accuracy. The proposed GWO-based version is discretized into a binary tool through the transformation function. We evaluate the performance of the new feature selection method based on 24 UCI data sets.​ Experimental results show that the developed algorithm performs better than the original technique, and the defects are resolved. Besides, we could reach higher classification accuracy and fewer feature selections than other optimization algorithms. A narrative web service at http://aliasgharheidari.com will offer the required data and material about this work.

Evolutionary biogeography-based whale optimization methods with communication structure: Towards measuring the balance

Abstract: Whale Optimization Algorithm (WOA) is a popular swarm-based algorithm with some spotted defects in its generated patterns during the searching phases. In this study, an enhanced WOA-based method is proposed in order to overcome the drawbacks of slow convergence speed and easy falling of WOA into the local optimum. The designed variant is called enhanced WOA (EWOA), which combines two strategies at the same time. First, a new communication mechanism (CM) is embedded into the basic WOA to promote the global optimal search ability and the exploitation tendency of the WOA. Then, the Biogeography-based Optimization (BBO) algorithm is partially utilized to harmonize the exploration and exploitation trends. A representative set of comprehensive benchmark cases and three engineering cases are utilized to verify the advantages of the proposed EWOA. The experimental results show that the exploration ability, exploitation ability, state of the balance, and convergence style of the algorithm has been improved significantly. Based on results, the proposed EWOA is a promising and excellent algorithm, and it has achieved better solution quality and faster convergence rate compared with other most advanced algorithms. For access to material and guide for users of this paper, we host an online page at https://aliasgharheidari.com .

Double adaptive weights for stabilization of moth flame optimizer: Balance analysis, engineering cases, and medical diagnosis

Abstract: Moth flame optimization (MFO) is a swarm-based algorithm with mediocre performance and marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode of moth lateral positioning. The basic MFO has no specific, deep strategies in different periods of the algorithm and a fragile evolutionary basis, which may lead to the problem of falling into local optimum and slow convergence trend. Therefore, this paper introduces a double adaptive weight mechanism into the MFO algorithm, termed as WEMFO, to boost the search capability of the basic MFO and provide a more efficient tool for optimization purposes. The proposed WEMFO adjusts the search strategy adaptively in different periods of the algorithm, making it more flexible between global search (diversification) and local search (intensification). The WEMFO algorithm is compared with some illustrious metaheuristic solvers and advanced metaheuristic methods developed in recent years on thirty benchmark functions. The experimental results expose that the developed WEMFO has apparent compensations in terms of convergence speed and solution accuracy. Moreover, this paper analyzes the diversity and balance of WEMFO and applies the algorithm to several engineering problems. The experimental results show that the WEMFO algorithm has good performance in engineering problems. Additionally, the proposed WEMFO was also applied to train Kernel Extreme Learning Machine (KELM), the resultant optimized WEMFO-KELM model was applied to six clinical disease classification problems. By comparing with MFO-KELM and other five classification models, the experimental results showed that the proposed algorithm had shown better performance in practical problems. An online guide for the algorithm in this research WEMFO and proposed classifier WEMFO-KELM will be publicly available at https://aliasgharheidari.com .

A computational framework for propagated waves in a sandwich doubly curved nanocomposite panel

Abstract: In the current report, characteristics of the propagated wave in a sandwich structure with a soft core and multi-hybrid nanocomposite (MHC) face sheets are investigated. The higher-order shear deformable theory (HSDT) is applied to formulate the stresses and strains. Rule of the mixture and modified Halpin–Tsai model are engaged to provide the effective material constant of the multi-hybrid nanocomposite face sheets of the sandwich panel. By employing Hamilton’s principle, the governing equations of the structure are derived. Via the compatibility rule, the bonding between the composite layers and a soft core is modeled. Afterward, a parametric study is carried out to investigate the effects of the CNTs' weight fraction, core to total thickness ratio, various FG face sheet patterns, small radius to total thickness ratio, and carbon fiber angel on the phase velocity of the FML panel. The results show that the sensitivity of the phase velocity of the FML panel to the $${W}_{\rm{CNT}}$$ and different FG face sheet patterns can decrease when we consider the core of the panel more much thicker. It is also observed that the effects of fiber angel and core to total thickness ratio on the phase velocity of the FML panel are hardly dependent on the wavenumber. The presented study outputs can be used in ultrasonic inspection techniques and structural health monitoring.