scholarly journals Numerical and experimental validation with bifurcation diagrams for a controlled DC–DC converter with quasi-sliding control

TecnoLógicas ◽  
2018 ◽  
Vol 21 (42) ◽  
pp. 147-167 ◽  
Author(s):  
Fredy E. Hoyos ◽  
John E. Candelo-Becerra ◽  
Nicolás Toro
Keyword(s):  
Output Voltage ◽  
Control Parameter ◽  
Experimental Validation ◽  
Chaotic Behavior ◽  
Previous Analysis ◽  
Buck Converter ◽  
Source Voltage ◽  
Simulation Results ◽  
The Stability ◽  
Transient And Steady State

This paper presents a stability analysis of a buck converter using a Zero Average Dynamics (ZAD) controller and Fixed-Point Induction Control (FPIC) when the control parameter 𝑁, the reference voltage υref, and the source voltage 𝐸 are changed. The study was based on a previous analysis in which the control parameter was adjusted to 𝑁=1 and the parameter 𝐾𝑠 was changed during the simulation, finding the stability zone and regions with chaotic behavior. Thus, this new study presents the transient and steady-state behaviors and robustness of the buck converter when the control parameter 𝑁 changes. Moreover, numerical simulation results are compared with experimental observations. The results show that the system regulates the output voltage with low error when the voltage is changed in the source E. Besides, the voltage overshoot increases, and the settling time decreases when the control parameter 𝑁 is augmented and the control parameter 𝐾𝑠 is constant. Furthermore, the buck converter controlled by ZAD and FPIC techniques is effective in regulating the output voltage of the circuit even when there are two delay periods and voltage input disturbances.

scholarly journals Fuzzy Logic Based Controller For Buck Converter

2019 ◽  
Vol 1 (3) ◽  
pp. 1-12
Author(s):  
Habibullah Salim ◽  
Irma Husnaini ◽  
Asnil Asnil
Keyword(s):  
Fuzzy Logic ◽  
Solar Cell ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Pulse Generation ◽  
Buck Converter ◽  
Dc Voltage ◽  
Generation Technique ◽  
Fuzzy Logic Method ◽  
The Stability

This research aims to make buck converter prototype for PLTS system by using fuzzy logic controller. Buck converter is required in the PLTS system if the required unidirectional voltage is smaller than the output voltage of the solar cell. Buck converter used to convert 24 Volt dc voltage to 12 Volt dc with 60 watt capability. While fuzzy logic controller is used to improve buck converter performance based on pulse generation technique for switching. The application of fuzzy logic method is expected to improve the performance of the system by maintaining the stability of buck converter output voltage of 12 volts and reduce the output ripple value. Atmega8535 microcontroller is used to generate PWM pulses for switching on power circuits. The results obtained from the test using a 100 Ohm 5 Watt load obtained the buck converter output voltage of 12.4 Volt.

Investigation of Thermal Effect of Packaged CMOS Compatible Pressure Sensor

Manufacturing ◽  
2002 ◽  
Author(s):  
Chih-Tang Peng ◽  
Ji-Cheng Lin ◽  
Chun-Te Lin ◽  
Kuo-Ning Chiang
Keyword(s):  
Pressure Sensor ◽  
Output Voltage ◽  
Experimental Validation ◽  
Experimental Result ◽  
Pressure Loading ◽  
Simulation Data ◽  
Sensor Performance ◽  
Piezoresistive Pressure Sensor ◽  
Simulation Results ◽  
Stress Buffer

In this study, a packaged silicon base piezoresistive pressure sensor with thermal stress buffer is designed, fabricated, and measured. A finite element method (FEM) is adopted for design and experimental validation of the sensor performance. Thermal and pressure loading on the sensor is applied to make a comparison between sensor experimental and simulation results. Furthermore, a method that transfers simulation stress data into output voltage is proposed in this study, the results indicate that the experimental result coincides with simulation data.

scholarly journals Análisis de estabilidad de convertidores de segundo orden con la metodología de optimización de suma de polinomios cuadráticos

2020 ◽  
Vol 1 (1) ◽  
pp. 49-58
Author(s):  
Jhon Jairo Herrera-Pérez ◽  
Alejandro Garcés-Ruiz
Keyword(s):  
Output Voltage ◽  
Equilibrium Points ◽  
Linear Method ◽  
Pi Controller ◽  
Quadratic Lyapunov Function ◽  
Boost Converters ◽  
Dc Microgrids ◽  
Practical Applications ◽  
Simulation Results ◽  
The Stability

This paper presents a non-linear method based on sum-of-squares (SOS), to determine the stability of equilibrium points for the Buck, Boost, Buck-Boost and non-inverter Buck-Boost converters. These converters share a similar structure with a PI controller to regulate the output voltage. A quadratic Lyapunov function is proposed in all cases, and the conditions for stability are evaluated using convex optimization based on SOS models. The methodology is useful for academic purposes but also in practical applications like DC microgrids. Simulation results shows the advantages of the proposed method.

Analysis of Changes in Temperature and Irradiance to DC-DC Buck Converter Based on IP Controller for Solar Power Plant Application

2015 ◽  
Vol 785 ◽  
pp. 127-130
Author(s):  
Slamet ◽  
Rasli bin Abd Ghani ◽  
Fuminori Kobayashi
Keyword(s):  
Mathematical Model ◽  
Power Plant ◽  
Input Signal ◽  
Output Voltage ◽  
Solar Power ◽  
Buck Converter ◽  
Solar Power Plant ◽  
Temperature Changes ◽  
C Programming ◽  
Simulation Results

This paper presents a mathematical model of photovoltaic with buck converter to analyze the voltage and current as a result of radiation and temperature changes as the input signal. Photovoltaic simulator models created using the C programming integrated with Matlab Simulink. The IP controller is used to control the current of a buck converter with the reference current from the dynamic model of photovoltaic. The control signal from the IP controller is used for generating a PWM signal, which is used to drive the IGBT gate of the buck converter. Input of irradiance and temperature are given to the photovoltaic simulator. Moreover, the current and voltage of the buck converter are used as a feedback to the photovoltaic simulator. This experiment is run through the system in real time and the simulation results show that changing in radiation has more significant effect on the output voltage of a solar power system compared to changing in temperature.

scholarly journals Fuzzy Logic Based Controller for Buck Converter

2018 ◽  
Author(s):  
Asnil ◽  
Habibullah ◽  
Irma Husnaini
Keyword(s):  
Fuzzy Logic ◽  
Solar Cell ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Pulse Generation ◽  
Buck Converter ◽  
Dc Voltage ◽  
Generation Technique ◽  
Fuzzy Logic Method ◽  
The Stability

This research aims to make buck converter prototype for PLTS system by using fuzzy logic controller. Buck converter is required in the PLTS system if the required unidirectional voltage is smaller than the output voltage of the solar cell. Buck converter used to convert 24 Volt dc voltage to 12 Volt dc with 60 watt capability. While fuzzy logic controller is used to improve buck converter performance based on pulse generation technique for switching. The application of fuzzy logic method is expected to improve the performance of the system by maintaining the stability of buck converter output voltage of 12 volts and reduce the output ripple value. Atmega8535 microcontroller is used to generate PWM pulses for switching on power circuits.

scholarly journals Analyses and Control of Chaotic Behavior in DC-DC Converters

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Cheng-Biao Fu ◽  
An-Hong Tian ◽  
Kuo-Nan Yu ◽  
Yi‐Hung Lin ◽  
Her-Terng Yau
Keyword(s):  
Fuzzy Control ◽  
Phase Plane ◽  
Chaotic Behavior ◽  
Nonlinear Behavior ◽  
Absolute Error ◽  
Input Voltage ◽  
Buck Converter ◽  
Simulation Results ◽  
And Control ◽  
Better Than

In this study the nonlinear behavior of a buck converter was simulated and the responses of Phases 1 and 2 and the chaotic phase were investigated using changes of input voltage. After a dynamic system model had been acquired using basic electronic circuit theory, Matlab and Pspice simulations were used to study system inductance, resistance, and capacitance. The characteristic changes of input voltage, and phase plane traces from simulation and experiments showed nonlinear behavior in Phases 1 and 2, as well as a chaotic phase. PID control and Integral Absolute Error (IAE) were used as adaption coefficients to control chaotic behavior, and particle swarm optimization (PSO) and the genetic algorithm were used to find the optimal gain parameters for the PID controller. Simulation results showed that the control of chaotic phenomena could be achieved and errors were close to zero. Fuzzy control was also used effectively to prevent chaos. The experimental results also showed nonlinear behavior from Phases 1 and 2 as well as the chaotic phase. Laboratory experiments conducted using both PID and fuzzy control echoed the simulation results. The fuzzy control results were somewhat better than those obtained with PID.

scholarly journals Controlling of DC-DC Buck Converters Using Microcontrollers

2021 ◽  
Vol 15 ◽  
pp. 197-202
Author(s):  
Mohammed O. Alsumady ◽  
Yazan K. Alturk ◽  
Ahmad Dagamseh ◽  
Ma'moun Tantawi
Keyword(s):  
Output Voltage ◽  
High Efficiency ◽  
Voltage Regulation ◽  
Buck Converter ◽  
Buck Converters ◽  
Voltage Variation ◽  
Digital Potentiometer ◽  
Digitally Controlled ◽  
Load Regulation ◽  
Source Voltage

This paper presents a technique to digitally control the output voltage of a DC-DC converter via a microcontroller. The voltage regulation and controlling were achieved utilizing an LM2596 buck converter. A digital potentiometer MCP41050 is utilized to smoothly control the regulated output DC voltage via the SPI digital protocol. The proposed design is manufactured and tested for various loads. This device is considered as a step-down voltage regulator capable of driving 3A load with high efficiency, excellent linearity, source-voltage variation, and load regulation. The results show that the system can control the output voltage with satisfactory performance and high accuracy. With various loads, the proposed system shows a mean square error of 0.015±0.037 volts tested with a regulated voltage of 5 volts. The efficiency improves from about 80% to around 91% at a 1 kΩ load. This design eliminates the possible errors that arise when manually varying the voltage of the buck converter; by means of using a microcontroller. Such a system ensures a proper digitally controlled output voltage with a better performance, which can be applied in various applications.

The Tangled Tale of Phase Space

2018 ◽  
Author(s):  
David D. Nolte
Keyword(s):  
Phase Space ◽  
Chaotic Behavior ◽  
Three Body Problem ◽  
Henri Poincaré ◽  
History Of ◽  
The Stability ◽  
Three Body ◽  
Space Phase ◽  
Central Paradigm ◽  
System Phase

This chapter presents the history of the development of the concept of phase space. Phase space is the central visualization tool used today to study complex systems. The chapter describes the origins of phase space with the work of Joseph Liouville and Carl Jacobi that was later refined by Ludwig Boltzmann and Rudolf Clausius in their attempts to define and explain the subtle concept of entropy. The turning point in the history of phase space was when Henri Poincaré used phase space to solve the three-body problem, uncovering chaotic behavior in his quest to answer questions on the stability of the solar system. Phase space was established as the central paradigm of statistical mechanics by JW Gibbs and Paul Ehrenfest.

scholarly journals Analysis and Design for Output Voltage Regulation in Constant-on-Time-Controlled Fly-Buck Converter

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1886
Author(s):  
Younghoon Cho ◽  
Paul Jang
Keyword(s):  
Output Voltage ◽  
Voltage Regulation ◽  
Design Guidelines ◽  
Buck Converter ◽  
Design Guideline ◽  
Analysis And Design ◽  
Flyback Converter ◽  
Auxiliary Power ◽  
Primary Output ◽  
Output Capacitor

Fly-buck converter is a multi-output converter with the structure of a synchronous buck converter structure on the primary side and a flyback converter structure on the secondary side, and can be utilized in various applications due to its many advantages. In terms of control, the primary side of the fly-buck converter has the same structure as a synchronous buck converter, allowing the constant-on-time (COT) control to be applied to the fly-buck converter. However, due to the inherent energy transfer principle, the primary-side output voltage regulation of COT controlled fly-buck converters may be poor, which can deteriorate the overall converter performance. Therefore, the primary output capacitor must be carefully designed to improve the voltage regulation characteristics. In this paper, a theoretical analysis of the output voltage regulation in COT controlled fly-buck converter is conducted, and based on this, a design guideline for the primary output capacitor considering the output voltage regulation is presented. The validity of the analysis and design guidelines was verified using a 5 W prototype of the COT controlled fly-buck converter for telecommunication auxiliary power supply.

scholarly journals Prediction and Stability Assessment of Soft Foundation Settlement of the Fishbone-Shaped Dike Near the Estuary of the Yangtze River Using Machine Learning Methods

2021 ◽  
Vol 13 (7) ◽  
pp. 3744
Author(s):  
Mingcheng Zhu ◽  
Shouqian Li ◽  
Xianglong Wei ◽  
Peng Wang
Keyword(s):  
Extreme Learning Machine ◽  
Prediction Models ◽  
Good Prediction ◽  
Foundation Settlement ◽  
Machine Method ◽  
Settlement Prediction ◽  
Soft Foundation ◽  
Simulation Results ◽  
Learning Machine ◽  
The Stability

Fishbone-shaped dikes are always built on the soft soil submerged in the water, and the soft foundation settlement plays a key role in the stability of these dikes. In this paper, a novel and simple approach was proposed to predict the soft foundation settlement of fishbone dikes by using the extreme learning machine. The extreme learning machine is a single-hidden-layer feedforward network with high regression and classification prediction accuracy. The data-driven settlement prediction models were built based on a small training sample size with a fast learning speed. The simulation results showed that the proposed methods had good prediction performances by facilitating comparisons of the measured data and the predicted data. Furthermore, the final settlement of the dike was predicted by using the models, and the stability of the soft foundation of the fishbone-shaped dikes was assessed based on the simulation results of the proposed model. The findings in this paper suggested that the extreme learning machine method could be an effective tool for the soft foundation settlement prediction and assessment of the fishbone-shaped dikes.

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