scholarly journals Piezoelectric Hysteresis Modeling of Hybrid Driven Three-Dimensional Elliptical Vibration Aided Cutting System Based on an Improved Flower Pollination Algorithm

Micromachines ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1532
Author(s):  
Xifeng Fu ◽  
Hong Gong ◽  
Mingming Lu ◽  
Jiakang Zhou ◽  
Jieqiong Lin ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Model Identification ◽  
Flower Pollination Algorithm ◽  
Model Parameters ◽  
Flower Pollination ◽  
Elliptical Vibration ◽  
Hysteresis Modeling ◽  
Modeling Accuracy ◽  
Cutting System ◽  
Hysteresis Characteristics

Three-dimensional elliptical vibration assisted cutting technology has been widely used in the past few years. The piezoelectric stack drive structure is an important part of the three-dimensional elliptical vibration aided cutting system. Its piezoelectric hysteresis characteristics affects the final output of the elliptical trajectory. Aiming at this problem, a piezoelectric hysteresis modeling method based on a generalized Bouc–Wen model is presented in this paper. An improved flower pollination algorithm (IFPASO) was used to identify Bouc–Wen model parameters. Standard test result shows that IFPASO has better algorithm performance. The model identification effect experiment proved that the Bouc–Wen model obtained by IFPASO identification, the highest modeling accuracy of the three axial subsystems, can reach 98.86%. Therefore, the model can describe the piezoelectric hysteresis characteristics of the three axial subsystems of the 3D-EVC system effectively and has higher modeling accuracy and fitting accuracy.

General Review of Calibration Process of Nonlinear Muskingum Model and Its Optimization by Up-to-Date Methods

2020 ◽  
pp. 61-83
Author(s):  
Umut Kırdemir ◽  
Umut Okkan
Keyword(s):  
Water Cycle ◽  
Search Algorithm ◽  
Flood Routing ◽  
Flower Pollination Algorithm ◽  
Model Parameters ◽  
Flower Pollination ◽  
Muskingum Model ◽  
Colliding Bodies Optimization ◽  
Nonlinear Muskingum Model ◽  
Outflow Hydrograph

Nonlinear Muskingum method is a very efficient tool in flood routing implementation. It is possible to estimate an outflow hydrograph by a given inflow hydrograph of a flood at a specific point of the river channel. However, it turns out an optimization problem at the stage of employing this method, and it becomes important to reach the optimal model parameters so as to obtain precise outflow hydrograph estimations. Hence, it was decided to utilize five up-to-date optimization algorithms, namely, vortex search algorithm (VSA), gases brownian motion algorithm (GBMO), water cycle algorithm (WCA), flower pollination algorithm (FPA), and colliding bodies optimization (CBO). The algorithms were integrated with the nonlinear Muskingum model so as to estimate the outflow hydrograph of Wilson data, and it was deduced that WCA, FPA, and VSA perform relatively better than the models employed in the other researches before.

An Improved Flower Pollination Algorithm for Optimal Unmanned Undersea Vehicle Path Planning Problem

2016 ◽  
Vol 30 (04) ◽  
pp. 1659010 ◽  
Author(s):  
Yongquan Zhou ◽  
Rui Wang
Keyword(s):  
Path Planning ◽  
Three Dimensional ◽  
Optimization Method ◽  
Population Based ◽  
Flower Pollination Algorithm ◽  
Planning Problem ◽  
Flower Pollination ◽  
3D Space ◽  
Undersea Vehicle ◽  
Path Planning Problem

Path planning of Unmanned Undersea Vehicle (UUV) is a rather complicated global optimum problem which is about seeking a superior sailing route considering the different kinds of constrains under complex combat field environment. Flower pollination algorithm (FPA) is a new optimization method motivated by flower pollination behavior. In this paper, a variant of FPA is proposed to solve the UUV path planning problem in two-dimensional (2D) and three-dimensional (3D) space. Optimization strategies of particle swarm optimization are applied to the local search process of IFPA to enhance its search ability. In the progress of iteration of this improved algorithm, a dimension by dimension based update and evaluation strategy on solutions is used. This new approach can accelerate the global convergence speed while preserving the strong robustness of standard FPA. The realization procedure for this improved flower pollination algorithm is also presented. To prove the performance of this proposed method, it is compared with nine population-based algorithms. The experiment result shows that the proposed approach is more effective and feasible in UUV path planning in 2D and 3D space.

scholarly journals Hysteresis Modeling and Compensation of Fast Steering Mirrors with Hysteresis Operator Based Back Propagation Neural Networks

Micromachines ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 732
Author(s):  
Kairui Cao ◽  
Guanglu Hao ◽  
Qingfeng Liu ◽  
Liying Tan ◽  
Jing Ma
Keyword(s):  
Neural Network ◽  
Back Propagation ◽  
Hysteresis Model ◽  
Cooperative Movement ◽  
Hysteresis Operator ◽  
The Neural Network ◽  
Hysteresis Nonlinearity ◽  
Hysteresis Modeling ◽  
Hysteresis Characteristics ◽  
Inverse Hysteresis

Fast steering mirrors (FSMs), driven by piezoelectric ceramics, are usually used as actuators for high-precision beam control. A FSM generally contains four ceramics that are distributed in a crisscross pattern. The cooperative movement of the two ceramics along one radial direction generates the deflection of the FSM in the same orientation. Unlike the hysteresis nonlinearity of a single piezoelectric ceramic, which is symmetric or asymmetric, the FSM exhibits complex hysteresis characteristics. In this paper, a systematic way of modeling the hysteresis nonlinearity of FSMs is proposed using a Madelung’s rules based symmetric hysteresis operator with a cascaded neural network. The hysteresis operator provides a basic hysteresis motion for the FSM. The neural network modifies the basic hysteresis motion to accurately describe the hysteresis nonlinearity of FSMs. The wiping-out and congruency properties of the proposed method are also analyzed. Moreover, the inverse hysteresis model is constructed to reduce the hysteresis nonlinearity of FSMs. The effectiveness of the presented model is validated by experimental results.

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