Fuzzy logic control to suppress noises and coupling effects in a laser tracking system

2005 ◽  
Vol 13 (1) ◽  
pp. 113-121 ◽  
Author(s):  
Ying Bai ◽  
Hanqi Zhuang ◽  
Z.S. Roth
2021 ◽  
Author(s):  
Oleg Samarin

his study investigates the applicability of fuzzy logic control to high-frame rate stereovision object tracking. The technology developed in this work is based on utilizing a disparity map produced by the Stereovision Tracking System (STS) to identify the object of interest. The coordinates of the object are used by the fuzzy logic control system to provide rotation and focus control for object tracking. The fuzzy logic control was realized as a reconfigurable hardware module and implemented on Virtex-2 FPGA platform of the STS. The fuzzy reasoning was implemented as a reconfigurable look-up table residing in FPGA's internal memory. A set of software tools facilitating creation of loop-up table and reconfiguration of fuzzy logic control system was developed. Finally, the experimental prototype of the system was built and tested.


Author(s):  
Ricardo Antonio-Mendez ◽  
Jesus de la Cruz-Alejo ◽  
Ollin Peñaloza-Mejia

Author(s):  
Kwangsoo Kim ◽  
Yongsoon Eun ◽  
Jaehong Park ◽  
Chang-hun Lee ◽  
Dong-il Dan Cho

2021 ◽  
Author(s):  
Oleg Samarin

his study investigates the applicability of fuzzy logic control to high-frame rate stereovision object tracking. The technology developed in this work is based on utilizing a disparity map produced by the Stereovision Tracking System (STS) to identify the object of interest. The coordinates of the object are used by the fuzzy logic control system to provide rotation and focus control for object tracking. The fuzzy logic control was realized as a reconfigurable hardware module and implemented on Virtex-2 FPGA platform of the STS. The fuzzy reasoning was implemented as a reconfigurable look-up table residing in FPGA's internal memory. A set of software tools facilitating creation of loop-up table and reconfiguration of fuzzy logic control system was developed. Finally, the experimental prototype of the system was built and tested.


2020 ◽  
Vol 190 ◽  
pp. 00004
Author(s):  
Chairul Imron ◽  
Imam Abadi ◽  
Nurika Brillianti ◽  
Muhammad Khamim Asy’ari ◽  
Yusilawati Ahmad Nor ◽  
...  

The changes in the intensity of solar radiation cause the electrical power produced by solar panels to be not optimal. The solar panel position control system to the position of the solar is an effort to overcome this problem. There are four Light Dependent Resistor (LDR) sensors placed on the sides of the four cardinal directions. The difference in the intensity of solar radiation received by each sensor causes the position of the solar panel to turn perpendicular to the position of the solar. The control method used is fuzzy logic control with three membership functions. The controlled variables are pitch angle and yaw angle in an active two-axis solar tracking system. Input fuzzy logic control is an error, and output is PWM. The results of the performance of the pitch angle control system produce settling time for 10 s and error steady-state obtained by 0.080 %, while for the yaw angle control system produces settling time for 13 s and steady-state error is obtained at 0.038 %. The existence of a control system resulted in an increase in the percentage of power above 30 % with a power difference of 7.49 W to a fixed panel.


Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory


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