scholarly journals Hybrid posicast controller for a DC-DC buck converter

2008 ◽  
Vol 5 (1) ◽  
pp. 121-138 ◽  
Author(s):  
Udhayakumar Kaithamalai ◽  
Lakshmi Ponnusamy ◽  
Boobal Kandasamy
Keyword(s):  
Natural Frequency ◽  
Traditional Method ◽  
Pid Controller ◽  
Feedback Loop ◽  
Buck Converter ◽  
Step Response ◽  
Loop Design ◽  
Hybrid Controller ◽  
Damped System ◽  
Lower Noise

A new Posicast compensated hybrid controller for the DC-DC Buck converter is investigated. Posicast is a feed forward compensator, which eliminates the overshoot in the step response of a lightly damped system. However, the traditional method is sensitive to variations in natural frequency. The new method described here reduces this undesirable sensitivity by using Posicast within the feedback loop. Design of the Posicast function is independent of computational delay. The new controller results in a lower noise in the control signal, when compared to a conventional PID controller.

scholarly journals Fractional-Order Approximation and Synthesis of a PID Controller for a Buck Converter

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 629 ◽  
Author(s):  
Allan G. Soriano-Sánchez ◽  
Martín A. Rodríguez-Licea ◽  
Francisco J. Pérez-Pinal ◽  
José A. Vázquez-López
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Order Approximation ◽  
Buck Converter ◽  
Step Response ◽  
Pid Controllers ◽  
Limited Frequency ◽  
Tuning Process ◽  
Band Limited ◽  
Fractional Order Pid

In this paper, the approximation of a fractional-order PIDcontroller is proposed to control a DC–DC converter. The synthesis and tuning process of the non-integer PID controller is described step by step. A biquadratic approximation is used to produce a flat phase response in a band-limited frequency spectrum. The proposed method takes into consideration both robustness and desired closed-loop characteristics, keeping the tuning process simple. The transfer function of the fractional-order PID controller and its time domain representation are described and analyzed. The step response of the fractional-order PID approximation shows a faster and stable regulation capacity. The comparison between typical PID controllers and the non-integer PID controller is provided to quantify the regulation speed introduced by the fractional-order PID approximation. Numerical simulations are provided to corroborate the effectiveness of the non-integer PID controller.

scholarly journals Model Direct Adaptive Control of Buck Converter by using MRAC

2019 ◽  
Vol 8 (12) ◽  
pp. 1108-1112
Keyword(s):  
Adaptive Control ◽  
Pid Controller ◽  
Buck Converter ◽  
Settling Time ◽  
Step Response ◽  
Control Parameters ◽  
Simple Shape ◽  
Model Reference ◽  
Direct Adaptive Control ◽  
Ascent Time

DC-DC converters are commonly implemented in effective packages. One of the regular varieties of DC-DC converters is dollar converter. The flexible controller techniques can decorate framework reaction not just like PID controller with steady parameter isn't hearty enough. The temporary reaction of PID controller exhibitions is multiplied depending on versatile issue. That lets in you to determine excellent placing for the control parameters underneath a few circumstance, a bendy element relying on MIT popular is carried out. Direct MRAC has a simple shape and wonderful execution in a few scenario. The proposed framework is regular and geared up to reach on the reaction of model reference superbly. Be that as it is able to, the react of the framework has straight away overshoot and pursue again the reaction of model reference. The ascent time, settling time, overshoot, and unfaltering country for step response are some destinations that decide if the adjustment additions art work as it should be. The confinement of bendy manage is the choice of the adjustment profits. The adjustment additions of the controller parameters are gotten with the aid of experimental increases.

scholarly journals Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3385
Author(s):  
Erickson Puchta ◽  
Priscilla Bassetto ◽  
Lucas Biuk ◽  
Marco Itaborahy Filho ◽  
Attilio Converti ◽  
...  
Keyword(s):  
Pid Controller ◽  
Optimization Algorithms ◽  
Optimization Methods ◽  
Buck Converter ◽  
Algebraic Solution ◽  
Nonlinear Load ◽  
Bee Colony ◽  
Arduous Task ◽  
Whale Optimization

This work deals with metaheuristic optimization algorithms to derive the best parameters for the Gaussian Adaptive PID controller. This controller represents a multimodal problem, where several distinct solutions can achieve similar best performances, and metaheuristics optimization algorithms can behave differently during the optimization process. Finding the correct proportionality between the parameters is an arduous task that often does not have an algebraic solution. The Gaussian functions of each control action have three parameters, resulting in a total of nine parameters to be defined. In this work, we investigate three bio-inspired optimization methods dealing with this problem: Particle Swarm Optimization (PSO), the Artificial Bee Colony (ABC) algorithm, and the Whale Optimization Algorithm (WOA). The computational results considering the Buck converter with a resistive and a nonlinear load as a case study demonstrated that the methods were capable of solving the task. The results are presented and compared, and PSO achieved the best results.

scholarly journals Optimal Fractional PID Controller for Buck Converter Using Cohort Intelligent Algorithm

2021 ◽  
Vol 4 (3) ◽  
pp. 50
Author(s):  
Preeti Warrier ◽  
Pritesh Shah
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Power Converters ◽  
Buck Converter ◽  
Optimization Techniques ◽  
Superior Performance ◽  
Computational Time ◽  
Optimization Approach ◽  
Response Characteristics ◽  
Fractional Order Controller

The control of power converters is difficult due to their non-linear nature and, hence, the quest for smart and efficient controllers is continuous and ongoing. Fractional-order controllers have demonstrated superior performance in power electronic systems in recent years. However, it is a challenge to attain optimal parameters of the fractional-order controller for such types of systems. This article describes the optimal design of a fractional order PID (FOPID) controller for a buck converter using the cohort intelligence (CI) optimization approach. The CI is an artificial intelligence-based socio-inspired meta-heuristic algorithm, which has been inspired by the behavior of a group of candidates called a cohort. The FOPID controller parameters are designed for the minimization of various performance indices, with more emphasis on the integral squared error (ISE) performance index. The FOPID controller shows faster transient and dynamic response characteristics in comparison to the conventional PID controller. Comparison of the proposed method with different optimization techniques like the GA, PSO, ABC, and SA shows good results in lesser computational time. Hence the CI method can be effectively used for the optimal tuning of FOPID controllers, as it gives comparable results to other optimization algorithms at a much faster rate. Such controllers can be optimized for multiple objectives and used in the control of various power converters giving rise to more efficient systems catering to the Industry 4.0 standards.

Synthesis Design and Analysis of a Hybrid Controller for Robotic Arms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Adaptive Controller ◽  
Convergence Speed ◽  
Model Reference ◽  
Robotic Arms ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

In this paper, a hybrid controller for robotic arms is proposed and designed by combining a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the model reference adaptive controller and the PID+MRAC hybrid controller for 1-DOF and 2-DOF manipulators are compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+MRAC controllers are better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

Design, analysis and modelling of a hybrid controller for serial robotic manipulators

Robotica ◽  
2016 ◽  
Vol 35 (9) ◽  
pp. 1888-1905 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Robotic Manipulators ◽  
Convergence Speed ◽  
Model Reference ◽  
Control Approach ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

SUMMARYWhen the end-effector of a robotic arm grasps different payload masses, the output of joint motion will vary. By using a model reference adaptive control approach, the payload variation effect can be solved. This paper describes the design for a hybrid controller for serial robotic manipulators by combining a PID controller and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators is compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+ MRAC controllers is better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

scholarly journals Modified Elman Neural-PID Controller Design for DC-DC Buck Converter System Based on Dolphin Echolocation Optimization

2018 ◽  
Vol 14 (3) ◽  
pp. 129-140
Author(s):  
Khulood E. Dagher
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Load Resistance ◽  
Buck Converter ◽  
Minimum Problem ◽  
Portable Devices ◽  
Elman Neural Network ◽  
Pid Controller Design ◽  
On Line ◽  
Local Minimum Problem

This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performance and achieve the desired output. In addition, there is a minimization for the tracking voltage error to zero value of the Buck converter output, especially when changing a load resistance by 10%.

scholarly journals The RHIC low level RF feedback loop design

1995 ◽  
Author(s):  
E. Onillon ◽  
J. M. Brennan
Keyword(s):  
Feedback Loop ◽  
Low Level ◽  
Loop Design

scholarly journals A correction in feedback loop applied to two-axis gimbal stabilization

2015 ◽  
Vol 63 (1) ◽  
pp. 217-219
Author(s):  
C. Zych ◽  
A. Wrońska-Zych ◽  
J. Dudczyk ◽  
A. Kawalec
Keyword(s):  
Working Conditions ◽  
Input Signal ◽  
Pid Controller ◽  
Feedback Loop ◽  
Measurement Unit ◽  
Observation System ◽  
Proportional Integral Derivative ◽  
Earned Value ◽  
Angular Velocities ◽  
Measurement Units

Abstract A two-axis gimbal system can be used for stabilizing platform equipped with observation system like cameras or different measurement units. The most important advantageous of using a gimbal stabilization is a possibility to provide not disturbed information or data from a measurement unit. This disturbance can proceed from external working conditions. The described stabilization algorithm of a gimbal system bases on a regulator with a feedback loop. Steering parameters are calculated from quaternion transformation angular velocities received from gyroscopes. This data are fed into the input of Proportional Integral Derivative (PID) controller. Their input signal is compared with earned value in the feedback loop. The paper presents the way of increasing the position’s accuracy by getting it in the feedback loop. The data fusion from a positioning sensor and a gyroscope results in much better accuracy of stabilization.

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