Feature Extraction for Excavator Operation Skill Using CMAC

2016 ◽  
Vol 28 (5) ◽  
pp. 715-721 ◽  
Author(s):  
Kazushige Koiwai ◽  
◽  
Yuntao Liao ◽  
Toru Yamamoto ◽  
Takao Nanjo ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Pid Controller ◽  
Cerebellar Model Articulation Controller ◽  
Proportional Integral Derivative ◽  
Control Engineering ◽  
Text Feature ◽  
Operation Techniques ◽  
Human Skills ◽  
The Difference ◽  
Variation Tendency

[abstFig src='/00280005/14.jpg' width='300' text='Feature extraction for excavator operation' ] In recent years, technology that includes informatization and automation has been introduced in the construction field. On the other hand, those field still require human operation technology based on experience and skills because various environmental conditions vary from hour to hour. Seasoned technicians have made such operation technology effective at various sites and established skillful techniques. However, the decreasing number and aging of skilled technicians are a social issue, making the skill tradition and development of younger technicians difficult at operation sites that require skillful techniques. This study assumed that the operation of machines by an operator was synonymous with the control of systems by a controller; human operation techniques were considered from the viewpoint of control engineering by regarding an operator as a controller. The control system used to represent the operator consisted of a proportional-integral-derivative (PID) controller and a cerebellar model articulation controller (CMAC) that adjusted the PID gains. A CMAC which is a type of neural network learns human skills as variations in the PID gains and expresses them based on the variations. This study applies the proposed method to a hydraulic excavator swing operation to evaluate skills. Moreover, the difference in the operation skills for the excavator is clarified by obtaining operation data for skilled and younger technicians and examining the variation tendency of PID gains.

Establishment and comparison of a spatial dynamics model for virtual track train with different steering modes

2021 ◽  
pp. 146441932110240
Author(s):  
Zhonghui Yin ◽  
Jiye Zhang ◽  
Haiying Lu
Keyword(s):  
Pid Controller ◽  
Dynamic Performance ◽  
Spatial Dynamics ◽  
Steering System ◽  
Front Wheel ◽  
Proportional Integral Derivative ◽  
Dynamics Model ◽  
Proposed Model ◽  
Suspension Control ◽  
Curved Section

To solve the urbanization and the economic challenges, a virtual track train (VTT) transportation system has been proposed in China. To evaluate the dynamic behavior of the VTT, a spatial dynamics model has been developed that considers the suspension system and the steering system. Additionally, the model takes into account road irregularity to make simulations more realistic. Based on the newly proposed dynamic model and a designed proportional–integral–derivative (PID) controller, simulation frames of the vehicle and of the VTT are established with the path-tracking performance. The results show that the vehicle and the VTT can run along a desired lane with allowable errors, verifying the proposed model. The vehicle and VTT with the four-wheel steering system show a better dynamic performance than the models with the front-wheel steering system in the curved section. Moreover, the simulation frame can be further applied to dynamics-related assessments, parameter optimization and active suspension control strategy.

Design of Text Categorization System Based on SVM

2012 ◽  
Vol 532-533 ◽  
pp. 1191-1195 ◽  
Author(s):  
Zhen Yan Liu ◽  
Wei Ping Wang ◽  
Yong Wang
Keyword(s):  
Feature Extraction ◽  
Feature Selection ◽  
Text Categorization ◽  
Feature Selection Method ◽  
Extraction Methods ◽  
Support Vector ◽  
Text Representation ◽  
Text Feature ◽  
Categorization System ◽  
Classifier Training

This paper introduces the design of a text categorization system based on Support Vector Machine (SVM). It analyzes the high dimensional characteristic of text data, the reason why SVM is suitable for text categorization. According to system data flow this system is constructed. This system consists of three subsystems which are text representation, classifier training and text classification. The core of this system is the classifier training, but text representation directly influences the currency of classifier and the performance of the system. Text feature vector space can be built by different kinds of feature selection and feature extraction methods. No research can indicate which one is the best method, so many feature selection and feature extraction methods are all developed in this system. For a specific classification task every feature selection method and every feature extraction method will be tested, and then a set of the best methods will be adopted.

An H∞ Design Approach for a PID Automatic Flight Control System of a Launch Vehicle

2016 ◽  
Vol 859 ◽  
pp. 116-123
Author(s):  
Adrian Mihail Stoica ◽  
Mihaela Raluca Stefanescu
Keyword(s):  
Flight Control ◽  
Pid Controller ◽  
Design Methodology ◽  
Launch Vehicle ◽  
Proportional Integral Derivative ◽  
Flight Control System ◽  
Numerical Examples ◽  
Stability Robustness ◽  
Norm Minimization ◽  
Atmospheric Disturbances

The paper presents a design methodology for the automatic flight control of a launch vehicle. In the proposed approach the controller has a PID (Proportional-Integral-Derivative) structure but its gains are determined solving an H∞ norm minimization problem of the mapping from the atmospheric disturbances to the control amplitude and to the angle of attack of the launcher. The design methodology is illustrated by numerical examples in which both time responses and stability robustness properties of the optimal PID controller are analyzed.

PSO-Based Tunning of PID Controller for Speed Control of DC Motor

2014 ◽  
Vol 7 (3) ◽  
pp. 65-79
Author(s):  
Ibrahem S. Fatah
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Dc Motor ◽  
Proportional Integral Derivative ◽  
Stable Convergence ◽  
Swarm Optimization ◽  
Tuning Parameters ◽  
Pid Controller Tuning ◽  
Rising Time

In this paper, a Proportional-Integral-Derivative (PID) controller of DC motor is designed by using particle swarm optimization (PSO) strategy for formative optimal PID controller tuning parameters. The proposed approach has superior feature, including easy implementation, stable convergence characteristics and very good computational performances efficiency. The DC Motor Scheduling PID-PSO controller is modeled in MATLAB environment. Comparing with conventional PID controller using Genetic Algorithm, the planned method is more proficient in improving the speed loop response stability, the steady state error is reduced, the rising time is perfected and the change of the required input do not affect the performances of driving motor with no overtaking.

A method of version merging for computer-aided design files based on feature extraction

2010 ◽  
Vol 225 (2) ◽  
pp. 463-471 ◽  
Author(s):  
C Sun ◽  
D Guo ◽  
H Gao ◽  
L Zou ◽  
H Wang
Keyword(s):  
Feature Extraction ◽  
Computer Aided Design ◽  
Application Programming Interface ◽  
Difference Set ◽  
Computer Aided ◽  
Application Programming ◽  
Feature Difference ◽  
The Difference ◽  
Aided Design ◽  
The Given

In order to manage the version files and maintain the latest version of the computer-aided design (CAD) files in asynchronous collaborative systems, one method of version merging for CAD files is proposed to resolve the problem based on feature extraction. First of all, the feature information is extracted based on the feature attribute of CAD files and stored in a XML feature file. Then, analyse the feature file, and the feature difference set is obtained by the given algorithm. Finally, the merging result of the difference set and the master files with application programming interface (API) interface functions is achieved, and then the version merging of CAD files is also realized. The application in Catia validated that the proposed method is feasible and valuable in engineering.

scholarly journals SAR Image Change Detection Based on Multi-scale Feature Extraction

2021 ◽  
Vol 10 (4) ◽  
pp. 077-081
Author(s):  
Xiaoqian Yuan ◽  
Chao Chen ◽  
Shan Tian ◽  
Jiandan Zhong
Keyword(s):  
Feature Extraction ◽  
Change Detection ◽  
Speckle Noise ◽  
Kernel Matrix ◽  
Sar Image ◽  
Scale Feature ◽  
Difference Image ◽  
Multi Scale ◽  
Image Change Detection ◽  
The Difference

In order to improve the contrast of the difference image and reduce the interference of the speckle noise in the synthetic aperture radar (SAR) image, this paper proposes a SAR image change detection algorithm based on multi-scale feature extraction. In this paper, a kernel matrix with weights is used to extract features of two original images, and then the logarithmic ratio method is used to obtain the difference images of two images, and the change area of the images are extracted. Then, the different sizes of kernel matrix are used to extract the abstract features of different scales of the difference image. This operation can make the difference image have a higher contrast. Finally, the cumulative weighted average is obtained to obtain the final difference image, which can further suppress the speckle noise in the image.

scholarly journals Performance Evaluation of Fractional Order Pid and Sliding Mode Control with Optimization Tuning Access

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1448-1454
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
World Economy ◽  
Sliding Mode ◽  
Proportional Integral Derivative ◽  
Robust Controller ◽  
The Past ◽  
Control Schemes ◽  
Different Types ◽  
Fractional Order Pid

The statistical analyses in the past showing the important properties of the electrohydraulic actuator (EHA) system, especially in the growth of the world economy. Dealing with the existing drawback in the EHA system, various types of control schemes have been introduced in the past. In this paper, to produce a more insightful view of the performance and the capabilities of the controller, three different types of controllers have been designed and compared. The favourite controller in the industry field, which is the proportional-integral-derivative (PID) controller will be first introduced. Follow by the improved PID controller, named Fractional Order (FO-PID) controller will be designed. Then, the prominent robust controller in the control field, called sliding mode controller (SMC) will be established. Instead of obtaining the controller’s parameters without any appropriate technique, the well-known tuning technique in computer science, named particle swarm optimization (PSO) will be utilized. Referring to the performances produced by these controllers, it can be concluded that the SMC is capable to generate most desired control performance that produced the highest accuracy with the smallest error in the analyses.

scholarly journals Position Tracking of ML System using CSA Based PID Controller

2019 ◽  
Vol 8 (11) ◽  
pp. 1956-1959
Keyword(s):  
Pid Controller ◽  
Magnetic Levitation ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pid Controllers ◽  
Position Tracking ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Simulation Results

The classical proportional integral derivative (PID) controllers are still use in various applications in industry. Magnetic levitation (ML) systems are rigidly nonlinear and sometimes unstable systems. Due to inbuilt nonlinearities of ML systems, tracking of position of ML Systems is still difficult. For the tracking purpose of position, PID controller parameters are found by choosing Cuckoo Search Algorithm (CSA) of optimization. The ranges of parameters are customized by z-n method of parameters. Simulation results show the tracking of position of ML systems using conventional and optimized parameters obtained with the CSA based controller.

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