Adaptive controller design for speed control of DC motors driven by a DC-DC buck converter

Roy, T. K.; Paul, Liton Chandra; Sarkar, M. I.; Pervej, M. F.; Tumpa, F. K.

doi:10.1109/ecace.2017.7912888

Cited by 27 publications

(11 citation statements)

References 13 publications

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“…Let and is the velocity vector and position vector for agent or particle , respectively. 4 PIDF parameters to be adjusted, so the design parameter is stated in (8) Firstly, the particles velocity, and swarm particles, are set randomly using (9) and (10), respectively, where is an upper boundary and is a lower boundary set for the agents, while and is For this simulation, an enhanced PSO algorithm using a priority-based fitness technique is recommended for PIDF tuning [18]. Sum squared error (SSE) of angular velocity, is set as uppermost primacy and sum absolute error (SAE) of angular velocity is set as second priority.…”

Section: B Particle Swarm Optimization (Pso)mentioning

confidence: 99%

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PSO Fined-tuned Model-Free PID Controller with Derivative Filter for Buck-Converter Driven DC Motor

2019

IJRTE

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Traditionally, the PID controller parameters are tuned heuristically based on time response behavior of the system. This method is tiresome job and can cause undesirable system response. Therefore, this research suggests the tuning method of a model-free PID controller with derivative filter (PIDF) by implementing Particle Swarm Optimization (PSO). This tuning method is applied to buck-converter driven DC motor control. The speed of DC motor is controlled by PIDF controller. The parameters of PIDF controller are fine-tuned by implementing PSO algorithms. The fitness functions of the algorithm are evaluated based on Sum Square Error (SSE) and Sum Absolute Error (SAE). The state-space representation of buck-converter/DC motor is considered to confirm the design of the control method. The results of the proposed tuning method are compared with PI controller and PIDF controller tuned by PID Tuner Simulink. The time response specifications of angular velocity, armature current and duty cycle input energy are considered as a control scheme performance. Finally, the suggested tuning technique promises a very minimum duty cycle energy and a fast input tracking of DC motor angular velocity.

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Section: B Particle Swarm Optimization (Pso)mentioning

confidence: 99%

“…A considerable amount of literature has been published on control of buck-converter driven DC motor. For instance, H-infinity controller [6], data driven sigmoid-based PI controller [7], PI-fuzzy logic controller [8] and adaptive controller based on Lyapunov function [9].…”

Section: Introductionmentioning

confidence: 99%

PSO Fined-tuned Model-Free PID Controller with Derivative Filter for Buck-Converter Driven DC Motor

2019

IJRTE

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“…This system, in general, is composed of three stages, namely, a DC/DC Buck converter, a complete bridge inverter, and a DC motor. Unlike the arrangements presented in [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29], such configuration allows the bidirectional driving of the motor shaft. The system average model presented in Figure 1, which was deduced and experimentally validated in [35], is given by…”

Section: Systemmentioning

confidence: 99%

“…Another solution was proposed by Nizami et al in [24], where a neuro-adaptive backstepping control for the angular velocity tracking was developed for the aforementioned system. Other interesting works reported in the last months, on tracking control design for the DC/DC Buck-DC motor system, are [25][26][27][28][29]. Additional works where other topologies of DC/DC power converters driven DC motors are [30][31][32] for the Boost converter, [33] for the Buck-Boost converter, and [34] for the Sepic and Cuk converters.…”

Section: Introductionmentioning

confidence: 99%

Bidirectional Tracking Robust Controls for a DC/DC Buck Converter‐DC Motor System

et al. 2018

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Two differential flatness-based bidirectional tracking robust controls for a DC/DC Buck converter-DC motor system are designed. To achieve such a bidirectional tracking, an inverter is used in the system. First control considers the complete dynamics of the system, that is, it considers the DC/DC Buck converter-inverter-DC motor connection as a whole. Whereas the second separates the dynamics of the Buck converter from the one of the inverter-DC motor, so that a hierarchical controller is generated. The experimental implementation of both controls is performed via MATLAB-Simulink and a DS1104 board in a built prototype of the DC/DC Buck converter-inverter-DC motor connection. Controls show a good performance even when system parameters are subjected to abrupt uncertainties. Thus, robustness of such controls is verified.

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“…Alexandridis and Konstantopoulos [10] presented a nonlinear PI control that does not require current sensors for solving the regulation task, and the same authors developed a regulation nonlinear control that provides a closed-loop passive system that is robust to load variations [11]. Additional works in which different topologies of DC/DC power converters have been used in combination with a DC motor are the following: [12][13][14][15][16][17][18][19][20][21][22][23][24][25] for the buck converter, [26,27] for the buck-boost converter, and [28] for the SEPIC andĆuk converters. Because of the operation principle of the DC/DC converters, works reported in [7][8][9][10][11][12][13][14][15][16][17][18][19][20][26][27][28] were only focused on driving the motor shaft in an unidirectional fashion for solving both the regulation and tracking problems.…”

Section: Introductionmentioning

confidence: 99%

DC/DC Boost Converter–Inverter as Driver for a DC Motor: Modeling and Experimental Verification

et al. 2018

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In this paper, the modeling and the experimental verification of the “bidirectional DC/DC boost converter–DC motor” system are presented. By using circuit theory along with the model of a DC motor, the mathematical model of the system is derived. This model was experimentally tested under time-varying duty cycles obtained via the system differential flatness property. The experimental verification was carried out using Matlab-Simulink and a DS1104 board in a built prototype of the system.

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Adaptive controller design for speed control of DC motors driven by a DC-DC buck converter

Cited by 27 publications

References 13 publications

PSO Fined-tuned Model-Free PID Controller with Derivative Filter for Buck-Converter Driven DC Motor

PSO Fined-tuned Model-Free PID Controller with Derivative Filter for Buck-Converter Driven DC Motor

Bidirectional Tracking Robust Controls for a DC/DC Buck Converter‐DC Motor System

DC/DC Boost Converter–Inverter as Driver for a DC Motor: Modeling and Experimental Verification

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