scholarly journals Development of a DSP Microcontroller-Based Fuzzy Logic Controller for Heliostat Orientation Control

2020 ◽  
Vol 10 (5) ◽  
pp. 1598
Author(s):  
Eugenio Salgado-Plasencia ◽  
Roberto V. Carrillo-Serrano ◽  
Manuel Toledano-Ayala
Keyword(s):  
Fuzzy Logic ◽  
Digital Signal Processor ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Low Cost ◽  
Angular Position ◽  
Digital Signal ◽  
Orientation Control ◽  
Dc Motors

This paper describes the design and implementation of a heliostat orientation control system based on a low-cost microcontroller. The proposed system uses a fuzzy logic controller (FLC) with the Center of Sums defuzzification method embedded on a dsPIC33EP256MU806 Digital Signal Processor (DSP), in order to modify the orientation of a heliostat by controlling the angular position of two DC motors connected to the axes of the heliostat. The FLC is compared to a traditional Proportional-Integral-Derivative (PID) controller to evaluate the performance of the system. Both the FLC and PID controller were designed for the position control of the heliostat DC motors at no load, and then they were implemented in the orientation control of the heliostat using the same controller parameters. The experimental results show that the FLC has a better performance and flexibility than a traditional PID controller in the orientation control of a heliostat.

scholarly journals Modelling and Simulation of Stepper Motor For Position Control Using LabVIEW

1970 ◽  
Vol 5 (1.) ◽  
Author(s):  
Ahmet Mehmet Karadeniz ◽  
Malek Alkayyali ◽  
Péter Tamás Szemes
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Bond Graph ◽  
Industrial Applications ◽  
Modelling And Simulation ◽  
Stepper Motor ◽  
Stepping Motor ◽  
Better Than

This paper presents hybrid stepper motor (is a type of stepping motor) modelling and simulation which is widely used a kind of motor in industrial applications. In this study, the stepper motor was modelled using bond graph technique and simulation for desired position was executed on LabVIEWgraphical interface. Then, firstly a convenient PID controller was designed for position, speed and current and PID close loopresponse was obtained for position control. Then, PID parameters for each controller were arranged separately to obtain good response Secondly, Fuzzy Logic controller applied to the system and its response was obtained. Finally, both responses are compared. According to comparison, it was observed that Fuzzy Logic controller’s response is better than PID’s. (In this paper, all shown responses were observed for 120 degree desired position)

scholarly journals PID and Fuzzy Logic Controller Design for Balancing Robot Stabilization

2018 ◽  
pp. 1-10
Keyword(s):  
Fuzzy Logic ◽  
Tilt Angle ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Controller Design ◽  
Point Of View ◽  
Relative Advantage ◽  
Balancing Robot ◽  
Time Required

This paper addresses the problem of position control and stabilization for the two wheeled balancing robot. A mathematical model is derived based on the robot’s position and tilt angle and a fuzzy logic control is proposed for the balancing robot control. The fuzzy logic controller performance is compared with a conventional PID controller to show the difference between them. Both controllers were tested on the balancing robot in simulation using MATLAB software and the results were put together for a comparative point of view. The simulations shows a relative advantage for the fuzzy logic controller over the conventional PID controller especially in reducing the time required for stabilization which takes about 2 seconds and almost without overshoot while in the PID case the robot will have about 10% overshoot in position and about 20 degrees in tilt angle.

Development of Servo Drive Positioning Control System Using PID Controller and Fuzzy Logic Controller

2021 ◽  
Vol 26 (6) ◽  
pp. 583-588
Author(s):  
Zaw Myo Naing ◽  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Settling Time ◽  
Fuzzy Pid ◽  
Servo Drive ◽  
Positioning Control ◽  
Fuzzy Pid Controller

Servo drives are one of the most widely utilized devices in various mechanical systems and industrial applications to provide precise position control. The study of servo driver produc-tiveness and performance index is the important task. In this work, PID controller and fuzzy log-ic controller (FLC) were developed to control the position of a DC servo drive. The MATLAB Simulink program was investigated and implemented to calculate the values of servo drive pa-rameters, and a scheme for simulating the operation of a servo drive using different controllers was presented. A mathematical model of a DC servo drive for a positioning control system has been proposed. The control characteristics of the PID controller, fuzzy logic controller and fuzzy PID controller are compared. The simulation results have shown that the PID controller allows for an overshoot of about 1 % with a settling time of about 4 sec. The use of the fuzzy PID con-troller reduces the maximum overshoot to 1 % and decreases the settling time to 2 sec. As a re-sult, the fuzzy PID controller allows for better performance and efficiency compared to other controllers.

DEVELOPMENT OF SIMPLE FUZZY LOGIC CONTROLLER FOR EXTENDED PERIOD-ZCS/ZVS-QUASI RESONANT CONVERTER: DESIGN, SIMULATION, AND EXPERIMENTATION

2006 ◽  
Vol 15 (05) ◽  
pp. 757-776
Author(s):  
S. ARULSELVI ◽  
UMA GOVINDARAJAN
Keyword(s):  
Fuzzy Logic ◽  
Digital Signal Processor ◽  
Fuzzy Logic Controller ◽  
Computing Time ◽  
Experimental Studies ◽  
Extended Period ◽  
Digital Signal ◽  
Resonant Converter ◽  
Memory Space ◽  
Load Variations

This paper describes the design and implementation of simple fuzzy logic controller (SFLC) for a nonlinear quasi-resonant converter (QRC). It is shown that the two-dimensional rule table of conventional FLCs (CFLCs) used in power converters can be reduced to one-dimensional rule table using SFLC. The proposed SFLC reduces the memory space and computing time of the fuzzy algorithm. The tuning of scaling factors and the generation of fuzzy rules are also easier when compared with CFLC. As a result, realizing SFLC in a Microcontroller or Digital Signal Processor (DSP) is made simple. The proposed controller structure is universal and it can be directly applied to any of the dc–dc converter topologies. In this paper, the application of SFLC is successfully verified for the voltage control of Extended Period (EP)-ZCS/ZVS-QRC through simulation and experimental studies using TMS320F2407A Processor. The ability of SFLC, compared to CFLC, to achieve good transient response for load variations and supply disturbances is demonstrated.

scholarly journals SCADA-Based Heliostat Control System with a Fuzzy Logic Controller for the Heliostat Orientation

2019 ◽  
Vol 9 (15) ◽  
pp. 2966 ◽  
Author(s):  
Salgado-Plasencia ◽  
Carrillo-Serrano ◽  
Rivas-Araiza ◽  
Toledano-Ayala
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Mean Squared Error ◽  
Low Cost ◽  
Orientation Control ◽  
Wireless Communication Network ◽  
Remote Terminal ◽  
Control Command ◽  
Remote Terminal Unit

In central receiver systems, there are local controls that modify the position of the heliostats, where the trend is to increase the intelligence of the local controls in order to give them greater autonomy from the central control. This document describes the design and construction of a SCADA (Supervisory Control And Data Acquisition)-based heliostat control system (HCS) with a fuzzy logic controller (FLC) for the orientation control. The HCS includes a supervisory unit with a graphical user interface, a wireless communication network, and a stand-alone remote terminal unit (RTU) implemented on a low-cost microcontroller (MCU). The MCU uses a solar position algorithm with a maximal error of 0.0027° in order to compute the position of the sun and the desired angles of the heliostat, according to a control command sent by the supervisory unit. Afterwards, the FLC orients the heliostat to the desired position. The results show that the RTU can perform all the tasks and calculations for the orientation control by using only one low-cost microcontroller with a mean squared error less than 0.1°. Besides, the FLC orients the heliostat by using the same controller parameters in both axes. Therefore, it is not necessary to tune the controller parameters, as in the traditional PID (Proportional-Integral-Derivative) controllers. The system can be adapted in order to control other two-axis solar-tracking systems.

Digital Signal Processor Based Over-current Relay Using Fuzzy Logic Controller

2011 ◽  
Vol 39 (13) ◽  
pp. 1437-1451 ◽  
Author(s):  
Yin Lee Goh ◽  
Agileswari K. Ramasamy ◽  
Farrukh Hafiz Nagi ◽  
Aidil Azwin Zainul Abidin
Keyword(s):  
Fuzzy Logic ◽  
Digital Signal Processor ◽  
Fuzzy Logic Controller ◽  
Digital Signal ◽  
Signal Processor

Development of a fuzzy logic controller on a digital signal processor

1993 ◽  
Vol 39 (2-5) ◽  
pp. 277-280 ◽  
Author(s):  
I. del Campo ◽  
J.R.González de Mendívil ◽  
J.M. Tarela
Keyword(s):  
Fuzzy Logic ◽  
Digital Signal Processor ◽  
Fuzzy Logic Controller ◽  
Digital Signal ◽  
Signal Processor

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

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