scholarly journals Filtering a Signal in a Fuzzy Filter Based on the Area Ratio Method

2020 ◽  
Vol 24 (3) ◽  
pp. 183-195
Author(s):  
M. V. Bobyr ◽  
M. Yu. Luneva
Keyword(s):  
Kalman Filter ◽  
Digital Filter ◽  
Experimental Studies ◽  
Area Ratio ◽  
Center Of Gravity ◽  
Ratio Method ◽  
Fuzzy Filter ◽  
Signal Filtering ◽  
Gravity Method ◽  
Control Coefficients

Purpose of reseach. Digital signal filtering allows real-time noise reduction in electronic devices. Currently, there are many different digital filters, differing in speed, computing power, algorithms and restrictions on the conditions of use. One of these filters is the Kalman filter, but adjusting the gains of this filter is very complicated by the process of additional experiments and collection of statistical information. Therefore, in this paper, the authors consider a simplified algorithm for finding the control coefficients of a fuzzy digital filter with defuzzifier based on the area ratio method and investigate the influence of the area ratio method parameters on signal filtering, thereby achieving the goal of improving the accuracy of the fuzzy digital filter. Methods. For the algorithm for finding the control coefficients of the digital filter, a fuzzy logic apparatus was used. The control factors are determined using a defuzzifier based on the area ratio method. Results. In the course of experimental studies, the mean square error RMSE was calculated for a fuzzy digital filter using the area ratio method, the center of gravity method and the Kalman filter. Based on the results obtained, it was concluded that the fuzzy filter based on the area ratio RMSE method is 5.43 times less than for the Kalman filter and 2.77 times less than for the defuzzifier based on the center of gravity method. The results obtained prove the effectiveness of using a fuzzy digital filter with the area ratio method. Conclusion: This article considers an algorithm for the operation of a fuzzy digital filter, simulates a fuzzy digital filter and a Kalman filter in the Simulink system and calculates the RMSE values for a fuzzy digital filter with the area ratio method and the center of gravity method, as well as the Kalman filter.

ANALYSIS OF THE SPEED OF THE DEFUZZIFIER IN THE TASK OF CONTROLLING THE ROBOT-MANIPULATOR

2020 ◽  
pp. 18-28
Author(s):  
M. V. Bobyr ◽  
N. A. Milostnaya ◽  
A. E. Arkhipov ◽  
M. Yu. Luneva
Keyword(s):  
Simulation Model ◽  
Digital Filter ◽  
High Speed ◽  
Robot Manipulator ◽  
Computation Time ◽  
Robotic Manipulator ◽  
Center Of Gravity ◽  
Robotic Arm ◽  
Ratio Method ◽  
Gravity Method

Linear, nonlinear, modified, high-speed defuzzifiers based on the area ratio method are presented in this paper. The proposed defuzzifiers are used in a fuzzy digital filter device and make it possible to ensure the additivity of the robotic manipulator control system, since traditional models do not have this property. The essence of this development is to find a crisp value of the output fuzzy variable, which in this case are the regulation coefficients of the fuzzy digital filter. Reducing the number of computational operations provides an increase in the performance of the defuzzifier. The reduction in number of computational operations is carried out by eliminating the output variable’s truncated term’s height calculation, thereby reducing the computation time. A simulation model which was implemented in the MatLab Simulink system, for a neuro-fuzzy device of the robotic arm using linear and non-linear defuzzifiers is presented. The dependence of time graphs on the angle of rotation of the joints of the robotic manipulator are compared, based on the traditional center of gravity method and the method shown in this paper. It was found that the traditional center of gravity method does not ensure the fulfillment of the specified rotation angles of the links of the robotic arm, while the proposed models of defuzzifiers have this property, which can be seen from the presented dependency graphs. The simulation model of the device was also designed as a parallel-conveyor device for implementation in the field-programmable gate array of the Xilinx Spartan 3Е family. The analysis showed that the calculation time for a crisp value with high-speed defuzzification is 130 ns, which is two orders of magnitude higher than existing models. The experiment was conducted at a frequency of 100 MHz.

scholarly journals Shade recognition of the color label based on the fuzzy clustering

2021 ◽  
Vol 20 (2) ◽  
pp. 407-434
Author(s):  
Maxim Bobyr ◽  
Alexander Arkhipov ◽  
Aleksey Yakushev
Keyword(s):  
Fuzzy Clustering ◽  
Color Image ◽  
Vision System ◽  
Video Recording ◽  
Experimental Studies ◽  
Area Ratio ◽  
Center Of Gravity ◽  
Clustering Model ◽  
Technical Vision ◽  
Fuzzy Clustering Method

In this article the task of determining the current position of pneumatic actuators is considered. The solution to the given task is achieved by using a technical vision system that allows to apply the fuzzy clustering method to determine in real time the center coordinates and the displacement position of a color label located on the mechatronic complex actuators. The objective of this work is to improve the accuracy of the moving actuator’s of mechatronic complex by improving the accuracy of the color label recognition. The intellectualization of process of the color shade recognition is based on fuzzy clustering. First, a fuzzy model is built, that allows depending on the input parameters of the color intensity for each of the RGB channels and the color tone component, to select a certain color in the image. After that, the color image is binarized and noise is suppressed. The authors used two defuzzification models during simulation a fuzzy system: one is based on the center of gravity method (CoG) and the other is based on the method of area ratio (MAR). The model is implemented based on the method of area ratio and allows to remove the dead zones that are present in the center of gravity model. The method of area ratio determines the location of the color label in the image frame. Subsequently, when the actuator is moved longitudinally, the vision system determines the location of the color label in the new frame. The color label position offset between the source and target images allows to determine the moved distance of the color label. In order to study  how noise affects recognition accuracy, the following digital filters were used: median, Gaussian, matrix and binomial. Analysis of the accuracy of these filters showed that the best result was obtained when using a Gaussian filter. The estimation was based on the signal-to-noise coefficient. The mathematical models of fuzzy clustering of color label recognition were simulated in the Matlab/Simulink environment. Experimental studies of technical vision system performance with the proposed fuzzy clustering model were carried out on a pneumatic mechatronic complex that performs processing, moving and storing of details. During the experiments, a color label was placed on the cylinder, after which the cylinder moved along the guides in the longitudinal direction. During the movement, video recording and image recognition were performed. To determine the accuracy of color label recognition, the PSNR and RMSE coefficients were calculated which were equal 38.21 and 3.14, respectively. The accuracy of determining the displacement based on the developed model for recognizing color labels was equal 99.7%. The defuzzifier speed has increased to 590 ns.

scholarly journals Age determination of common bottlenose dolphins (Tursiops truncatus) using dental radiography pulp:tooth area ratio measurements

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242273
Author(s):  
Jean M. Herrman ◽  
Jeanine S. Morey ◽  
Ryan Takeshita ◽  
Sylvain De Guise ◽  
Randall S. Wells ◽  
...  
Keyword(s):  
Life Histories ◽  
Marine Mammals ◽  
Bottlenose Dolphins ◽  
Age Determination ◽  
Area Ratio ◽  
Dental Radiography ◽  
Ratio Method ◽  
Data Sets ◽  
Photo Identification ◽  
Development And Validation

Age is an important parameter to better understand wildlife populations, and is especially relevant for interpreting data for fecundity, health, and survival assessments. Estimating ages for marine mammals presents a particular challenge due to the environment they inhabit: accessibility is limited and, when temporarily restrained for assessment, the window of opportunity for data collection is relatively short. For wild dolphins, researchers have described a variety of age-determination techniques, but the gold-standard relies upon photo-identification to establish individual observational life histories from birth. However, there are few populations with such long-term data sets, therefore alternative techniques for age estimation are required for individual animals without a known birth period. While there are a variety of methods to estimate ages, each involves some combination of drawbacks, including a lack of precision across all ages, weeks-to-months of analysis time, logistical concerns for field applications, and/or novel techniques still in early development and validation. Here, we describe a non-invasive field technique to determine the age of small cetaceans using periapical dental radiography and subsequent measurement of pulp:tooth area ratios. The technique has been successfully applied for bottlenose dolphins briefly restrained during capture-release heath assessments in various locations in the Gulf of Mexico. Based on our comparisons of dental radiography data to life history ages, the pulp:tooth area ratio method can reliably provide same-day estimates for ages of dolphins up to about 10 years old.

Hybrid filters and feedback mechanism for wearable-based human-manipulator interface

2015 ◽  
Vol 42 (5) ◽  
pp. 485-495 ◽  
Author(s):  
Ping Zhang ◽  
Bei Li ◽  
Guanglong Du
Keyword(s):  
Kalman Filter ◽  
Measurement Errors ◽  
Unscented Kalman Filter ◽  
Robot Manipulator ◽  
Experimental Studies ◽  
Feedback Mechanism ◽  
Content Type ◽  
System States ◽  
Noisy Measurements ◽  
Hybrid Filters

Purpose – This paper aims to develop a wearable-based human-manipulator interface which integrates the interval Kalman filter (IKF), unscented Kalman filter (UKF), over damping method (ODM) and adaptive multispace transformation (AMT) to perform immersive human-manipulator interaction by interacting the natural and continuous motion of the human operator’s hand with the robot manipulator. Design/methodology/approach – The interface requires that a wearable watch is tightly worn on the operator’s hand to track the continuous movements of the operator’s hand. Nevertheless, the measurement errors generated by the sensor error and tracking failure signicantly occur several times, which means that the measurement is not determined with sufficient accuracy. Due to this fact, IKF and UKF are used to compensate for the noisy and incomplete measurements, and ODM is established to eliminate the influence of the error signals like data jitter. Furthermore, to be subject to the inherent perceptive limitations of the human operator and the motor, AMT that focuses on a secondary treatment is also introduced. Findings – Experimental studies on the GOOGOL GRB3016 robot show that such a wearable-based interface that incorporates the feedback mechanism and hybrid filters can operate the robot manipulator more flexibly and advantageously even if the operator is nonprofessional; the feedback mechanism introduced here can successfully assist in improving the performance of the interface. Originality/value – The interface uses one wearable watch to simultaneously track the orientation and position of the operator’s hand; it is not only avoids problems of occlusion, identification and limited operating space, but also realizes a kind of two-way human-manipulator interaction, a feedback mechanism can be triggered in the watch to reflect the system states in real time. Furthermore, the interface gets rid of the synchronization question in posture estimation, as hybrid filters work independently to compensate the noisy measurements respectively.

Comparison of the Kalman filter with classical digital filter

AIChE Journal ◽  
1974 ◽  
Vol 20 (3) ◽  
pp. 598-600 ◽  
Author(s):  
Robert G. Kneile ◽  
Richard H. Luecke
Keyword(s):  
Kalman Filter ◽  
Digital Filter

scholarly journals IMU-Based Online Kinematic Calibration of Robot Manipulator

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Guanglong Du ◽  
Ping Zhang
Keyword(s):  
Kalman Filter ◽  
Robot Manipulator ◽  
Experimental Studies ◽  
Estimation Method ◽  
Kinematic Parameter ◽  
Corner Detection ◽  
Measurement Unit ◽  
Robot Calibration ◽  
Self Calibration ◽  
Calibration Methods

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

Sign in / Sign up

Export Citation Format

Share Document