A Comparative Analysis of Integrated Boost Flyback Converter using PID and Fuzzy Controller

2015 ◽  
Vol 5 (4) ◽  
pp. 486
Author(s):  
R.Samuel Rajesh Babu
Keyword(s):  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Pid Controller ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Energy System ◽  
Flyback Converter ◽  
Integrated Boost ◽  
Simulation Results

<div class="Section1"><p class="papertitle">This paper presents a comparative analysis of Integrated boost flyback converter for Renewable energy System. IBFC is the combination of boost converter and fly back converter. The proposed converter is simulated in open and closed loop using PID and FUZZY controller. The Fuzzy Logic Controller (FLC) is used reduce the rise time, settling time to almost negligible and try to remove the delay time and inverted response. The performance of IBFC with fuzzy logic controller  is found better instead of PID controller. The simulation results are verified experimentally and  the output of converter is free from ripples and has regulated output voltage.</p></div>

scholarly journals Control of Rotary Cranes Using Fuzzy Logic

2001 ◽  
Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo
Keyword(s):  
Fuzzy Logic ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Building Construction ◽  
Loop Control ◽  
Industrial Structures ◽  
Inference Engines

Abstract Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them became difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control preferable. In this work a fuzzy logic controller is introduced with the idea of split-horizon; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FTEs). Computer simulations are used to verify the performance of the controller. Three simulation cases are introduced: radial, compound, and damping. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing them in a relatively reasonable time.

scholarly journals Fuzzy logic controller for closed loop cascaded flyback converter fed PMDC-motor system

2020 ◽  
Vol 11 (4) ◽  
pp. 1857
Author(s):  
C.T. Manikandan ◽  
G.T. Sundarrajan
Keyword(s):  
Fuzzy Logic ◽  
Time Domain ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Supply Voltage ◽  
Dc Voltage ◽  
Flyback Converter ◽  
Modeling Simulation ◽  
Motor Load ◽  
Time Domain Response

This paper displays a Fly Back Converter idea to straightforwardly incorporate cascaded flyback converter. The flyback-converter finds a way between DC-source and DC Motor-load. This work covenants with the modeling, simulation, and application of a Fuzzy Logic controlled (FLC) - Cascaded Fly back Converter (CFLB) system. This work recommends FLC to control Parallel cascaded fly-back converter to fabricate essential DC voltage from the input supply voltage. The yield of CFLB is controlled utilizing closed loop configuration. Closed loop PI &amp; Fuzzy logic controlled CFLB systems are simulated and their results are related. The outcomes signify that the FLC based system gave a superior response than the P.I. controlled CFLB system. The FLC controlled CFLB system has benefits like decreased steady state error and enhanced time domain-response.

scholarly journals Speed Control for DC Encoder Motor and Path Optimization in an Automated Guided Vehicle

2020 ◽  
Vol 9 (1) ◽  
pp. 977-980
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Optimal Path ◽  
Constant Speed ◽  
Path Optimization ◽  
Destination Node ◽  
Automated Guided Vehicle ◽  
Speed Response

Automated guided vehicle （AGV） has variety of applications in the field of automotive and logistics. For stability of plant AGV should run at a constant speed. The AGV incorporates DC encoder motor which is controlled by Fuzzy controller and PID controller to acquire the constant speed. Response of the system with of fuzzy controller and PID controller is done. . The steady state error and overshoot of the system is reduced by the fuzzy logic controller. Dijkstra’s algorithm is applied to find an optimal path. This algorithm finds the shortest path between the source node and destination node.

scholarly journals Intelligent Traffic Management Service Using Fuzzy Logic Controller in High Speed Networks

2019 ◽  
pp. 95-98
Author(s):  
Muppineni Sravanthi
Keyword(s):  
Fuzzy Logic ◽  
Traffic Management ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
System Simulation ◽  
Core Area ◽  
Management Service ◽  
High Speed Networks ◽  
Simulation Results

Network traffic management is a core area of research that is of great importance in the field of communication. This paper proposes a new scheme for controlling router side traffic in networks by updating source sending rate according to its IQ size. A new fuzzy controller is to be modelled to implement the proposed system. Simulation results and comparisons has verified the effectiveness and showed that our proposed scheme can achieve better performances than the existing protocols.

scholarly journals FPGA based co-design of a speed fuzzy logic controller applied to an autonomous car

2021 ◽  
Vol 10 (3) ◽  
pp. 195
Author(s):  
Emna Aridhi ◽  
Decebal Popescu ◽  
Abdelkader Mami
Keyword(s):  
Signal Processing ◽  
Fuzzy Logic ◽  
Digital Signal Processing ◽  
Ambient Temperature ◽  
Software Design ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Digital Signal ◽  
Execution Cycle ◽  
Simulation Results

This paper invests in FPGA technology to control the speed of an autonomous car using fuzzy logic. For that purpose, we propose a co-design based on a novel fuzzy controller IP. It was developed using the hardware language VHDL and driven by the Zynq processor through an SDK software design written in C. The proposed IP acts according to the ambient temperature and the presence or absence of an obstacle and its distance from the car. The partitioning of the co-design tasks divides them into hardware and software parts. The simulation results of the fuzzy IP and those of the complete co-design implementation on a Xilinx Zynq board showed the effectiveness of the proposed controller to meet the target constraints and generate suitable PWM signals. The proposed hardware architecture based on 6-LUT blocks uses 11 times fewer logic resources than other previous similar designs. Also, it can be easily updated when new constraints on the system are to be considered, which makes it suitable for many related applications. Fuzzy computing was accelerated thanks to the use of digital signal processing blocks that ensure parallel processing. Indeed, a complete execution cycle takes only 7 us.

Active Vibration Control of Piezoelectric Material Using Fuzzy Logic Controller

2014 ◽  
Vol 513-517 ◽  
pp. 2659-2662
Author(s):  
Tao Hu ◽  
Qi Bai Huang ◽  
Shan De Li
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Active Vibration Control ◽  
Structural Vibration ◽  
Resonant Response ◽  
Vibration Absorption ◽  
Active Vibration ◽  
The Subject

Active control of vibration has been the subject of a lot of research in recent years. This study presents a fuzzy logic controller (FLC) to minimize structural vibration using collocated piezoelectric actuator/sensor pairs. The proposed fuzzy controller increases the damping of the structures to minimize certain responses. The PID controller is used as a contrast controller to the FLC. The numerical simulation results show that the fuzzy approach is much portable than PID method. In summary, a novel vibration absorption scheme using fuzzy logic has been demonstrated to significantly enhance the performance of a flexible structure with resonant response.

scholarly journals Optimization of DC motor speed control based on fuzzy logic-PID controller

2021 ◽  
pp. 143-153
Author(s):  
Amer Farhan Sheet ◽  
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Fuzzy Rules ◽  
Motor Speed ◽  
Speed Error ◽  
Self Tuning ◽  
The Difference

In this paper the PID controller and the Fuzzy Logic Controller (FLC) are used to control the speed of separately excited DC motors. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to Fuzzy Logic rules. The FLC cotroller is designed according to fuzzy rules so that the system is fundamentally robust. Twenty-five fuzzy rules for self-tuning of each parameter of the PID controller are considered. The FLC has two inputs; the first one is the motor speed error (the difference between the reference and actual speed) and the second one is a change in the speed error (speed error derivative). The output of the FLC, i.e. the parameters of the PID controller, are used to control the speed of the separately excited DC Motor. This study shows that the precisiom feature of the PID controllers and the flexibllity feature of the fuzzy controller are presented in the fuzzy self-tuning PID controller. The fuzzy self – tuning approach implemented on the conventional PID structure improved the dynamic and static response of the system. The salient features of both conventional and fuzzy self-tuning controller outputs are explored by simulation using MATLAB. The simulation results demonstrate that the proposed self-tuned PID controller i.plementd a good dynamic behavior of the DC motor i.e. perfect speed tracking with a settling time, minimum overshoot and minimum steady state errorws.

A Control Strategy for Intelligent Stamp Forming Tooling

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
William J. Emblom ◽  
Klaus J. Weinmann
Keyword(s):  
Fuzzy Logic ◽  
Control Systems ◽  
Control Strategy ◽  
Pid Controller ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Linear Quadratic ◽  
Blank Holder ◽  
Loop Control ◽  
Stamp Forming

This paper describes the development and implementation of closed-loop control for oval stamp forming tooling using MATLAB®’s SIMULINK® and the dSPACE®CONTROLDESK®. A traditional PID controller was used for the blank holder pressure and an advanced controller utilizing fuzzy logic combining a linear quadratic gauss controller and a bang–bang controller was used to control draw bead position. The draw beads were used to control local forces near the draw beads. The blank holder pressures were used to control both wrinkling and local forces during forming. It was shown that a complex, advanced controller could be modeled using MATLAB’s SIMULINK and implemented in DSPACE CONTROLDESK. The resulting control systems for blank holder pressures and draw beads were used to control simultaneously local punch forces and wrinkling during the forming operation thereby resulting in a complex control strategy that could be used to improve the robustness of the stamp forming processes.

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