scholarly journals Visual positioning control of fuze detection manipulator

2021 ◽  
Vol 2125 (1) ◽  
pp. 012017
Author(s):  
An Zhang ◽  
Shaojie Ma ◽  
Libo Ding
Keyword(s):  
Control Algorithm ◽  
Detection Method ◽  
Fuzzy Controller ◽  
Dynamic Adjustment ◽  
Deviation Angle ◽  
Optimal Motion ◽  
Positioning Accuracy ◽  
Positioning Control ◽  
Visual Positioning ◽  
Motion Parameters

Abstract This paper designs a fuze automatic detection manipulator. Aiming at the problem of autonomous alignment and docking between operation manipulator and detection device, a visual positioning control algorithm for autonomous alignment between fuze and detection device based on fuzzy logic is proposed. Taking the relative position and deviation angle of fuze and detection device as control variables, a two-dimensional fuzzy controller is designed. Through the dynamic adjustment of the controller, the optimal motion parameters can be output. Compared with the traditional fuze detection method, the algorithm further improves the efficiency and positioning accuracy of fuze detection.

scholarly journals An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Jozef Živčák ◽  
Michal Kelemen ◽  
Ivan Virgala ◽  
Peter Marcinko ◽  
Peter Tuleja ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Mechanical Design ◽  
Mechanical Ventilator ◽  
Mechanical Ventilators ◽  
Inference System ◽  
Control Approach ◽  
Neuro Fuzzy

COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.

Multi-resolution Visual Positioning and Navigation Technique for Unmanned Aerial System Landing Assistance

2017 ◽  
Vol 70 (6) ◽  
pp. 1276-1292
Author(s):  
Chong Yu ◽  
Jiyuan Cai ◽  
Qingyu Chen
Keyword(s):  
Real World ◽  
State Of The Art ◽  
Unmanned Aerial System ◽  
Detection Accuracy ◽  
Relative Positioning ◽  
Positioning Accuracy ◽  
Visual Positioning ◽  
Positioning Technique ◽  
Technique Comparison ◽  
Resolution Simulation

To achieve more accurate navigation performance in the landing process, a multi-resolution visual positioning technique is proposed for landing assistance of an Unmanned Aerial System (UAS). This technique uses a captured image of an artificial landmark (e.g. barcode) to provide relative positioning information in the X, Y and Z axes, and yaw, roll and pitch orientations. A multi-resolution coding algorithm is designed to ensure the UAS will not lose the detection of the landing target due to limited visual angles or camera resolution. Simulation and real world experiments prove the performance of the proposed technique in positioning accuracy, detection accuracy, and navigation effect. Two types of UAS are used to verify the generalisation of the proposed technique. Comparison experiments to state-of-the-art techniques are also included with the results analysis.

Research on Fuzzy Control of Mine Ventilation Based on Embedded Systems

2014 ◽  
Vol 686 ◽  
pp. 126-131
Author(s):  
Xiao Yan Sha
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Simulation Analysis ◽  
Control Unit ◽  
Real Time Control ◽  
Embedded Processor ◽  
Feed Forward ◽  
Time Control ◽  
Software And Hardware

Taking embedded processor as the core control unit, the paper designs the fan monitoring system software and hardware to achieve the fan working condition detection and real-time control. For the control algorithm, the paper analyzes the fuzzy control system theory and composition, and then combined with tunnel ventilation particularity, introduce feed-forward model to predict the incremental acquisition of pollutants to reduce lag, combined with the system feedback value and the set value, by calculate of two independent computing fuzzy controller, and ultimately determine the number of units increase or decrease in the tunnel jet fans start and stop. Through simulation analysis, the introduction of a feed-forward signal, it can more effectively improve the capability of the system impact of interference.

scholarly journals Application of a WiFi/Geomagnetic Combined Positioning Method in a Single Access Point Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hongbin Pan ◽  
Yang Xiang ◽  
Jian Xiong ◽  
Yifan Zhao ◽  
Ziwei Huang ◽  
...  
Keyword(s):  
Nearest Neighbor ◽  
Detection Method ◽  
Access Point ◽  
Combination Method ◽  
Data Set ◽  
Positioning Accuracy ◽  
Multipath Effects ◽  
Positioning Method ◽  
Fingerprint Database ◽  
Mismatch Rate

Because of the particularity of urban underground pipe corridor environment, the distribution of wireless access points is sparse. It causes great interference to a single WiFi positioning method or geomagnetic method. In order to meet the positioning needs of daily inspection staff, this paper proposes a WiFi/geomagnetic combined positioning method. In this combination method, firstly, the collected WiFi strength data was filtered by outlier detection method. Then, the filtered data set was used to construct the offline fingerprint database. In the following positioning operation, the classical k -nearest neighbor algorithm was firstly used for preliminary positioning. Then, a standard circle was constructed based on the points obtained by the algorithm and the actual coordinate points. The diameter of the standard circle was the error, and the geomagnetic data were used for more accurate positioning in this circle. The method reduced the WiFi mismatch rate caused by multipath effects and improved positioning accuracy. Finally, a positioning accuracy experiment was performed in a single AP distribution environment that simulates a pipe corridor environment. The results proves that the WiFi/geomagnetic combined positioning method proposed in this paper is superior to the traditional WiFi and geomagnetic positioning methods in terms of positioning accuracy.

scholarly journals RESEARCH AND IMPROVEMENT OF PRECISE ANGLE CONTROL SYSTEM

2010 ◽  
Vol 2 (1) ◽  
pp. 95-98
Author(s):  
Sigitas Šakalinis
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Controller Design ◽  
Stepper Motor ◽  
Main Task ◽  
Test Rig ◽  
Positioning Accuracy ◽  
Technical University

The main task was investigation and precision improve­ment for a positioning drive, installed in a test rig for testing and calibration of the geodetic instruments at Vilnius Gediminas Technical University, Institute of Geodesy. Replacement of a stepper motor and a microstepping controller design increased positioning accuracy to 0.1''. Vibrations and noise of the test rig were significantly decreased using an optimized control algorithm, where resonating step frequencies were bypassed. The time of scale rotation between measurements (every 30°) achieved less than 1.5 min. Methods of the further precision improvement were selected, and this research is in progress now.

Simulation of a New Self-Structured Fuzzy Controller Applied to a Temperature Control Process

2013 ◽  
Vol 4 (3) ◽  
pp. 47-57
Author(s):  
Rafik Lasri ◽  
Ignacio Rojas ◽  
Héctor Pomares ◽  
M. Nemiche
Keyword(s):  
Real Time ◽  
Temperature Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Control Process ◽  
The Self ◽  
Fuzzy Controllers ◽  
Current State ◽  
Internal Parameters

A new methodology of Fuzzy Controllers that can change the internal parameters of the controller in real time is presented in this paper. The Self-structured algorithm is able to adapt their rules consequents and re-organize their MFs in real time according to the current state of the controlled plant. Via a simulation of a temperature control process, the authors have proved and demonstrated the effectiveness and usefulness of their control algorithm compared to a conventional FLC under the same condition and using the same Simulated plant.

scholarly journals Analysis and Adaptation of Q-Learning Algorithm to Expert Controls of a Solar Domestic Hot Water System

2019 ◽  
Vol 2 (2) ◽  
pp. 15 ◽  
Author(s):  
Bettoni ◽  
Soppelsa ◽  
Fedrizzi ◽  
del Toro Matamoros
Keyword(s):  
Control Algorithm ◽  
Fuzzy Controller ◽  
Learning Algorithm ◽  
Water System ◽  
Hot Water ◽  
Reference Case ◽  
Domestic Hot Water ◽  
Q Learning ◽  
Performance Factor ◽  
Seasonal Performance

This paper discusses the development of a coupled Q-learning/fuzzy control algorithm to be applied to the control of solar domestic hot water systems. The controller brings the benefit of showing performance in line with the best reference controllers without the need for devoting time to modelling and simulations to tune its parameters before deployment. The performance of the proposed control algorithm was analysed in detail concerning the input membership function defining the fuzzy controller. The algorithm was compared to four standard reference control cases using three performance figures: the seasonal performance factor of the solar collectors, the seasonal performance factor of the system and the number of on/off cycles of the primary circulator. The work shows that the reinforced learning controller can find the best performing fuzzy controller within a family of controllers. It also shows how to increase the speed of the learning process by loading the controller with partial pre-existing information. The new controller performed significantly better than the best reference case with regard to the collectors’ performance factor (between 15% and 115%), and at the same time, to the number of on/off cycles of the primary circulator (1.2 per day down from 30 per day). Regarding the domestic hot water performance factor, the new controller performed about 11% worse than the best reference controller but greatly improved its on/off cycle figure (425 from 11,046). The decrease in performance was due to the choice of reward function, which was not selected for that purpose and it was blind to some of the factors influencing the system performance factor.

Research on Piezoelectric Actuator Driving Method of Creep Resistance

2008 ◽  
Vol 594 ◽  
pp. 104-109
Author(s):  
Wei Fan ◽  
Xiao Fen Yu ◽  
De Bao Li
Keyword(s):  
Piezoelectric Actuator ◽  
Creep Resistance ◽  
Scientific Method ◽  
Characteristic Curve ◽  
Positioning Accuracy ◽  
Positioning Control ◽  
High Frequency Response ◽  
Creep Characteristics ◽  
Creep Characteristic ◽  
Two Stages

The piezoelectric actuator demonstrates superior characteristics of high displacement resolution, miniature size, high-frequency response, strong power, no generate heat etc, So it is used in nano systems widely. But its inherent hysteresis, creep and non-linearity affect positioning accuracy seriously. In this paper, through the investigative experiment of a large travel piezoelectric actuator worktable’s creep characteristics, creep characteristic curve and the rules of the piezoelectric actuator creep were found. Based on the rules of the piezoelectric actuator creep characteristics, the piezoelectric actuator creep resistance driving method of two-level reversely applied voltage could remarkably reduce the creep error of system, namely, applying stepped voltage reversely according to two stages. The experiments show that the creep error of the system has been reduced from 3.80% to 0.26%, the period of creep tends to be stable, and also has been shortened within 10 seconds. This driving method make the quick and precise piezoelectric actuator positioning control with large displacement become possible. It also provides further scientific method to amend and reduce the creep effect of piezoelectric actuator, and improves the positioning accuracy of the system.

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