Design of Dual-Sampling and Adaptive Predictive PID Controller for Buck DC–DC Converters

2019 ◽  
Vol 28 (11) ◽  
pp. 1950195
Author(s):  
Changyuan Chang ◽  
Jidong Liu
Keyword(s):  
Transient Response ◽  
Pid Control ◽  
Delay Time ◽  
Pid Controller ◽  
Recovery Time ◽  
Digital Controller ◽  
Transient Performance ◽  
Analog To Digital ◽  
Control Schemes ◽  
Digitally Controlled

In this paper, based on the combination scheme of dual-sampling and adaptive predictive PID control, a digital controller for improving the transient performance of Buck DC–DC converters is designed. Due to the inherent loop delay in analog-to-digital (A/D) conversion, the calculation process of the digital controller and digital pulse width modulator (DPWM) of conventional digitally-controlled Buck DC–DC converters limits the system bandwidth and this makes the transient response lower. The designed digital controller can reduce the delay time in analog-to-digital converter (ADC), the digital controller and DPWM of digitally-controlled Buck DC–DC converters. Adaptive predictive control is used to eliminate the delay time of ADC and the digital controller, while dual-sampling scheme is used to reduce the delay time of DPWM in this paper. These are two new control schemes, and they show better performance in improving the transient response than other existing control schemes. Both simulation and experimental results demonstrate that the designed digital controller based on dual-sampling and adaptive predictive PID control is effective in improving the transient performance of Buck DC–DC converters. During experimental verification, for a load step between 0.5[Formula: see text]A and 1.0[Formula: see text]A, the fastest transient recovery time and the overshoot voltage are found to be 102[Formula: see text][Formula: see text]s and 120[Formula: see text]mV, respectively. Compared with the conventional digital PID controller, the transient recovery time and the overshoot voltage of the digital controller designed in this paper are decreased by 40.0% and 27.3%, respectively.

scholarly journals DC Motor Speed Control using Internal Model Controller: Industrial Transformation Strategy

2020 ◽  
Vol 9 (5) ◽  
pp. 300-306
Keyword(s):  
Transfer Function ◽  
Pid Control ◽  
Pid Controller ◽  
Internal Model ◽  
Dc Motor ◽  
Motor Speed ◽  
Matlab Simulink ◽  
Dc Motors ◽  
Control Schemes ◽  
Motor Model

In developed nations, industries are made to function at control engineering costs via the use of appropriate control schemes for dc motors. This paper introduces the role played by dc motors in industries thereby necessitating the analysis and performance validation of dc motor in Internal Model Control (IMC) scheme as against the Proportional– Integral–Derivative (PID) control schemes that is widely used in most industries. Theories on dc motor model, PID and IMC controller were detailed to paved the way for the methodical approach of getting specifications and transfer function for a typical dc motor (model RMCS-3011). Matlab/Simulink software was then used to tune the PID controller for the purpose of finding the values of PID gains that meets the design requirements to achieve best performance, thereby enabling the simulation of the PID controller. Using Matlab m-file environment, IMC controller transfer function was generated and simulated. The IMC controller transfer function aimed at achieving a unity gain that tracks the set-point was approximately realized. In the realization process, it was obvious that a filter is required. The aim of this work is to evaluate the performance of the IMC controller over PID controller. Simulated plots in Matlab-Simulink using the PID gains for the PID controller, and time constants and filter order for the IMC were presented. The quantitative results of the IMC method when compared with that of PID control provides a commendable performance. However, the performance in terms of rise time is small and preferred with the use of Matlab-Simulink tuned PID controller. Conclusively, IMC controller would be the preferred controller where the robustness and accuracy of the dc motor speed control counts more than faster response

scholarly journals Sintesis Kendali PID Digital dengan Diskritisasi Langsung dan Backward Difference

2021 ◽  
Vol 9 (2) ◽  
pp. 467
Author(s):  
FENI ISDARYANI ◽  
MOHAMAD FADHILAH VIERI HESYA ◽  
FERIYONIKA FERIYONIKA
Keyword(s):  
Difference Equation ◽  
Pid Control ◽  
Difference Method ◽  
Rise Time ◽  
Computer Programming ◽  
Settling Time ◽  
Digital Controller ◽  
Discretization Method ◽  
Analog To Digital ◽  
Digital Pid

ABSTRAKKendali PID analog, yang realisasinya menggunakan komponen elektronika, memiliki keterbatasan yaitu nilai toleransi yang terbatas. Saat ini spesifikasi kontroler dituntut untuk dapat berkomunikasi dengan sistem yang lebih besar seperti SCADA dan DCS sehingga lebih cocok menggunakan pengendali digital. Penelitian ini menganalisis metode konversi PID analog ke digital agar dihasilkan difference equation yang dapat direalisasikan ke dalam pemrograman komputer. Metode yang dipakai adalah diskritisasi langsung dan Backward Difference. Perbandingan kedua metode dilakukan dengan menganalisis respons berdasarkan initial paramater yang dihasilkan oleh metode Ziegler Nichols. Hasil pengujian menunjukkan kendali PID diskrit menggunakan Backward Difference menghasilkan respons sistem yang lebih baik dibandingkan metode diskritisasi langsung dengan nilai Kp, Ti, dan Td adalah 50, 80 dan 0,001 menghasilkan respons dengan nilai rise time, settling time dan overshoot berturut-turut sebesar 33,66s, 90,39s dan 0,9%.Kata kunci: PID diskrit, diskritisasi langsung, Backward Difference, Ziegler Nichols ABSTRACTThe analog PID control, where its parameters are realised using the electronic component, has disadvantages due to the limitation of its tolerance value. Currently, the specifications of controller are required to be able to communicate with larger systems such as SCADA and DCS, therefore digital controller is more appropriate to use. This study analyzes the analog to digital PID conversion method to generate a difference equation that can be realized in computer programming. The direct discretization and Backward Difference method are used. Comparison of both methods is by analyzing response based on initial parameters obtained of Ziegler Nichols method. The results show that discrete PID control using the Backward Difference indicates a better response than using the direct discretization method with Kp, Ti, and Td values are 50, 80, and 0,001, respectively. Those parameters generate response with rise time, settling time, and overshoot values of 33,66s, 90,39s, and 0,9%, respectively.Keywords: discrete PID, direct discretization, Backward Difference, ZieglerNichols

Control of limit cycles in buck converters

2014 ◽  
Vol 33 (4) ◽  
pp. 1448-1461 ◽  
Author(s):  
Marissa Condon ◽  
Brendan Hayes
Keyword(s):  
Limit Cycles ◽  
Mathematical Analysis ◽  
Pid Control ◽  
Design Methodology ◽  
Buck Converter ◽  
Digital Controller ◽  
Buck Converters ◽  
Content Type ◽  
Comb Filters ◽  
Digitally Controlled

Purpose – The purpose of this paper is to investigate limit cycles in digitally Proportional, Integral and Derivative (PID) controlled buck regulators. Filtering is examined as a means of removing the limit cycles in digitally controlled buck regulators. Design/methodology/approach – The paper explains why limit cycles occur in a digitally PID controlled buck converter. It then proceeds to propose two filters for their elimination. Results indicate the effectiveness of each of the filters. Findings – The paper gives a mathematical analysis of the occurrence of limit cycles in digitally controlled PID buck regulators. It finds that notch and comb filters are effective for the purpose of eliminating limit cycles in buck regulators. Originality/value – The paper employs a model of the buck regulator inclusive of the inductor loss – this was not done to date for this type of work. The paper analyses PID control. This was not done in the manner given. The paper addresses filtering as a means of removing limit cycles. It examines the effect of changing the digital controller parameters on the requirements of the filters.

Water Temperature Control Using PID Control System Based on LabVIEW

2016 ◽  
Vol 4 (2) ◽  
pp. 35-46
Author(s):  
Ari Ramadhani
Keyword(s):  
Water Temperature ◽  
Pid Control ◽  
Temperature Sensor ◽  
Pid Controller ◽  
Current Flow ◽  
Electrical Energy ◽  
Heating Process ◽  
Water Heater ◽  
Digital Thermometer ◽  
Flow Through

Abstract - Automatic system have grown widespread across all sector so do water heater. Traditionally, heating water is done by utilizing fire as heat source. As the growing of technology, the heating process could be done by manipulating electrical energy by convert it to heat. Electrical energy is flown to a metal rod that contact directly with the water which increase the water temperature. On some case, appropiate water temperature is needed. Altough, a thermometer is needed to read the actual temperature as a feedback value for the system and a system that can control the electricity current flow through the heater that the heat produced is linear to the current flow. With implementing microcontroller as a process node for generating PWM signal, this problem can be solved. Also, Labview is needed as an interface for monitoring and bursting an output which have been processed by Proportional, Integral, and Devivative (PID) controller to producing accurate and stable heat. Based on the results of testing, the system is able to provide a rapid response to any changes that occur, both changes in set-point and changes in water temperature (actual value). Another test is done by comparing the temperature value detected by the temperature sensor in this device with an external digital thermometer placed in the same place, and from some of the tests the temperature value detected by the temperature sensor in this device has a difference of ± 0.19 ℃ with a digital thermometer. Keyword : Water Heater, Thermometer, Microcontroller, LabView, PID.

Straight-Move Robot Control System with LabView-Based Proportional Integral Derivative (PID) Control

2019 ◽  
Vol 3 (2) ◽  
pp. 13-24
Author(s):  
Andrean George W
Keyword(s):  
Pid Control ◽  
Rotational Speed ◽  
Pid Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Labview Software ◽  
Dc Motors ◽  
Dc Motor Control ◽  
Process System ◽  
Interface Devices

Abstract - Control and monitoring of the rotational speed of a wheel (DC motor) in a process system is very important role in the implementation of the industry. PWM control and monitoring for wheel rotational speed on a pair of DC motors uses computer interface devices where in the industry this is needed to facilitate operators in controlling and monitoring motor speed. In order to obtain the best controller, tuning the Integral Derifative (PID) controller parameter is done. In this tuning we can know the value of proportional gain (Kp), integral time (Ti) and derivative time (Td). The PID controller will give action to the DC motor control based on the error obtained, the desired DC motor rotation value is called the set point. LabVIEW software is used as a PE monitor, motor speed control. Keyword : LabView, Motor DC, Arduino, LabView, PID.

Optimal tuning of PID controller in time delay system: a review on various optimization techniques

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Thomas George ◽  
V. Ganesan
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Pid Controller ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Delay Systems ◽  
Pid Controllers ◽  
Time Delay Systems ◽  
Process Industries ◽  
First Order

AbstractThe processes which contain at least one pole at the origin are known as integrating systems. The process output varies continuously with time at certain speed when they are disturbed from the equilibrium operating point by any environment disturbance/change in input conditions and thus they are considered as non-self-regulating. In most occasions this phenomenon is very disadvantageous and dangerous. Therefore it is always a challenging task to efficient control such kind of processes. Depending upon the number of poles present at the origin and also on the location of other poles in transfer function different types of integrating systems exist. Stable first order plus time delay systems with an integrator (FOPTDI), unstable first order plus time delay systems with an integrator (UFOPTDI), pure integrating plus time delay (PIPTD) systems and double integrating plus time delay (DIPTD) systems are the classifications of integrating systems. By using a well-controlled positioning stage the advances in micro and nano metrology are inevitable in order satisfy the need to maintain the product quality of miniaturized components. As proportional-integral-derivative (PID) controllers are very simple to tune, easy to understand and robust in control they are widely implemented in many of the chemical process industries. In industries this PID control is the most common control algorithm used and also this has been universally accepted in industrial control. In a wide range of operating conditions the popularity of PID controllers can be attributed partly to their robust performance and partly to their functional simplicity which allows engineers to operate them in a simple, straight forward manner. One of the accepted control algorithms by the process industries is the PID control. However, in order to accomplish high precision positioning performance and to build a robust controller tuning of the key parameters in a PID controller is most inevitable. Therefore, for PID controllers many tuning methods are proposed. the main factors that lead to lifetime reduction in gain loss of PID parameters are described in This paper and also the main methods used for gain tuning based on optimization approach analysis is reviewed. The advantages and disadvantages of each one are outlined and some future directions for research are analyzed.

scholarly journals An Improved PID Controller for the Compliant Constant-Force Actuator Based on BP Neural Network and Smith Predictor

2021 ◽  
Vol 11 (6) ◽  
pp. 2685
Author(s):  
Guojin Pei ◽  
Ming Yu ◽  
Yaohui Xu ◽  
Cui Ma ◽  
Houhu Lai ◽  
...  
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Pid Control ◽  
Pid Controller ◽  
Experimental Validation ◽  
Control Method ◽  
Smith Predictor ◽  
Constant Force ◽  
Matlab Simulation ◽  
Adjustment Time

A compliant constant-force actuator based on the cylinder is an important tool for the contact operation of robots. Due to the nonlinearity and time delay of the pneumatic system, the traditional proportional–integral–derivative (PID) method for constant force control does not work so well. In this paper, an improved PID control method combining a backpropagation (BP) neural network and the Smith predictor is proposed. Through MATLAB simulation and experimental validation, the results show that the proposed method can shorten the maximum overshoot and the adjustment time compared with traditional the PID method.

scholarly journals Quadratic Model-Based Dynamically Updated PID Control of CSTR System with Varying Parameters

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 31
Author(s):  
Dushko Stavrov ◽  
Gorjan Nadzinski ◽  
Stojche Deskovski ◽  
Mile Stankovski
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Absolute Error ◽  
Error Model ◽  
Quadratic Model ◽  
Control Performance ◽  
Continuous Stirred Tank Reactor ◽  
Quadratic Error ◽  
Varying Parameters ◽  
Cstr System

In this paper, we discuss an improved version of the conventional PID (Proportional–Integral–Derivative) controller, the Dynamically Updated PID (DUPID) controller. The DUPID is a control solution which preserves the advantages of the PID controller and tends to improve them by introducing a quadratic error model in the PID control structure. The quadratic error model is constructed over a window of past error points. The objective is to use the model to give the conventional PID controller the awareness needed to battle the effects caused by the variation of the parameters. The quality of the predictions that the model is able to deliver depends on the appropriate selection of data used for its construction. In this regard, the paper discusses two algorithms, named 1D (one dimensional) and 2D (two dimensional) DUPID. Appropriate to their names, the former selects data based on one coordinate, whereas the latter selects the data based on two coordinates. Both these versions of the DUPID controller are compared to the conventional PID controller with respect to their capabilities of controlling a Continuous Stirred Tank Reactor (CSTR) system with varying parameters in three different scenarios. As a quantifying measure of the control performance, the integral of absolute error (IAE) metric is used. The results from the performed simulations indicated that the two versions of the DUPID controller improved the control performance of the conventional PID controller in all scenarios.

Simulation Analysis of Electro-Pneumatic Proportional Fuzzy-PID Control System Based on AMESim/Simulink

2014 ◽  
Vol 945-949 ◽  
pp. 2568-2572
Author(s):  
Si Yuan Wang ◽  
Guang Sheng Ren ◽  
Pan Nie
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Simulation Analysis ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Proportional Control ◽  
Fuzzy Pid Controller ◽  
Design Requirements ◽  
Set Up

The test rig for hydro-pneumatic converter used in straddle type monorail vehicles was researched, and its electro-pneumatic proportional control system was set up and simulated based on AMESim/Simulink. Compared fuzzy-PID (Proportion Integral Derivative) controller with PID controller through fuzzy logic tool box in Simulink, the results indicate that, this electro-pneumatic proportional control system can meet design requirements better, and fuzzy-PID controller has higher accuracy and stability than PID controller.

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