Model Of DC Motor Research Articles

Research on the Modelling of a Single-winding Bearingless Permanent Magnet Brushless DC Motor

This paper studies the radial suspension force mathematical model of a single-winding bearingless permanent magnet brushless DC motor, which provides a theoretical basis for the precise control of a single-winding motor. First, the physical structure of the single-winding BL-BLDC motor and the principle of radial suspension force generation are introduced. Then, the equivalent magnetic circuit method is used to establish the electromagnetic relationship inside the motor and the virtual displacement method is used to derive and calculate the mathematical model of the radial suspension force. The radial suspension force of the motor is composed of the force generated by the suspension force winding and the unbalanced magnetic pull force generated by the motor rotor deviating from the center position. Finally, the finite element analysis software is used to model and simulate the single-winding motor to analyze the change of the suspension force amplitude under different currents and the influence of different eccentric displacements on the unbalanced magnetic tension of the motor. The results show that the error between the simulation results obtained by the FEA and the theoretical calculation results of the mathematical model is small, which verifies the correctness of the radial suspension force mathematical model of the single-winding BL-BLDC motor.

A Novel Fractional-Order Multiple-Model Type-3 Fuzzy Control for Nonlinear Systems with Unmodeled Dynamics

In this paper, a novel control approach is proposed for a class of uncertain nonlinear system with unmodeled dynamics. Each output of the system is modeled by several first-order dynamic fractional-order fuzzy systems. The best dynamic model is selected at a period of time and the control signal is designed based on this model. The dynamic fractional-order models are based on the special case of general type-2 fuzzy systems which are called interval type-3 fuzzy logic systems (IT3FLSs). The adaptation laws for the consequent parameters of IT3FLSs are derived through stability analysis of the fractional-order systems based on the linear matrix inequality approach. The effectiveness of the proposed scheme is verified by normal simulation on the hyperchaotic Lorenz system with unmodeled dynamics, real-time simulation on the chaotic model of the brushless DC motors using Arduino boards and experimental examination on a heat transfer system with fully unknown dynamics.

Certain Investigation Of Real Time Networked Control Dc Motor Using Smith Predictor

In this paper, DC motor is controlled by direct structure Networked Control System (NCS) with smith predictor control strategy. Mathematical model of DC motor is identified by empirical model building and estimated Round Trip Time Delay (RTT) is considered as time delay which is induced by network. Delay time which is induced in Networked DC motor is compensated with the smith predictor controller then the designed controller algorithm is comparatively analyzed with conventional PI controller. The simulation results are formulated for identified motor model with real time network. In addition to that the hardware fabrication of real time Networked DC motor has been developed and the results of both the simulation and hardware implementation are compared.

Orbit Design and Trajectory Analysis of satellite in Low Earth Orbit

An Attitude control system for a satellite in low earth orbit is designed in this project. As a reference, CARTOSAT-2 is selected to design the AOCS. CARTOSAT-2 is located in LEO so it suits the needs of the projects. It is mainly used for mapping of urban, rural areas and wetlands in India. To design a basic AOCS, a DC motor based model is considered. Transfer functions of DC motor and satellite dynamics model are calculated using Laplace transformation. Stability of the system is checked by plotting poles and zeroes of the systems. PID controller is used to improve the overall stability of the system by decreasing the errors in the output of the system. The systems are subjected to sine and step inputs and responses are plotted in the form of graphs. The plots are studied using SciLab as the tool to design the block diagram and the control system for the AOCS. Scilab along with FlightGear is used to visualize the response of the system.

Design and Simulation of DC Motor Controller Based on the Fuzzy Control

The motor fuzzy controller was designed by the application of the principle of fuzzy logic based on the research of DC motor model. The simulation analysis of traditional control and fuzzy control were conducted by MATLAB simulation module, which illustrates the better control performance of fuzzy control method by comparison.

Algorithm for identification of DC motor parameters by method of dynamic expansion of regressor and mixing

Subject of Research. The paper considers the problem of identifying the parameters of various robotic objects. A DC motor is used as an example. Existing methods for identification of parameters require either a large amount of time for accurate determination of the required values or give an estimate with a large error. We propose to expand the application area of the identification algorithm by the method of Dynamic Regressor Extension and Mixing for control problems of robotic objects with a DC motor. Method. The first stage of Dynamic Regressor Extension and Mixing method generates to this procedure. Main Results. A new algorithm is proposed for identifying the parameters of DC motor models. It is shown that, when using the new approach, the fluctuations in parameter estimates are significantly lower, while the response time is much shorter. When using the gradient method, the transient time to estimate the signal parameters is 350 seconds, while for the Dynamic Regressor Extension and Mixing method this time does not exceed six seconds. Besides, Dynamic Regressor Extension and Mixing method has not got overshoot. Practical Relevance. The results of the work can be applied to the design of automatic control systems in control problems of electromechanical objects, including DC motors.new regression forms by applying a dynamic operator to the original regression data. Then, the required combination of new data is selected to obtain the final desired regression form. Standard parameter estimation methods are applied.

Static Output Feedback Quantized Control for Fuzzy Markovian Switching Singularly Perturbed Systems With Deception Attacks

This article focuses on static output feedback control for fuzzy Markovian switching singularly perturbed systems (FMSSPSs) with deception attacks and asynchronous quantized measurement output. Different from the previous work, both the logarithmic quantizer and the static output feedback controller are dependent on the operation system; by means of hidden Markov models, their modes run asynchronously with that of FMSSPSs. Additionally, the deception attacks are guided by a Bernoulli variable, and nonlinear characteristics are modeled by the Takagi–Sugeno fuzzy model. By resorting to a mode-dependent Lyapunov functional, several criteria are acquired and strictly <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(\mathscr {Q},\mathscr {S},\mathscr {R})\text{--}\gamma$</tex-math></inline-formula> -dissipative of FMSSPSs can be ensured. Finally, a dc motor model is expressed to illustrate the effectiveness of the asynchronous control scheme.

Simulation of electro-mechanical friction clutch control using proportional derivative plus conditional integral control scheme for automotive application

This paper explains simulation works carried out to evaluate the performance of proportional-integral-derivative-based (PID-based) controls in controlling the electro-mechanical friction clutch (EMFC) for engagement and disengagement. The EMFC model is developed in Matlab/Simulink comprising DC motor's model and power screw mechanism's model. Four controls; proportional-integral (PI), proportional-integral-derivative (PID), proportional (P) and proportional derivative (PD), are applied on the model using 6 mm as the set point for the power screw's position. Among them, PD control performs the best with 0% overshoot, 0.041 mm steady state error and about 1.3 seconds settling time. Next, the PD control is updated with a conditional integral controller (PDPCI), resulting in approximately zero steady state error and only 0.68% overshoot, while settling time stays at 1.3 seconds. Subsequently, both PD and PDPCI controls are simulated to achieve EMFC's full engagement and disengagement. The final results show that PDPCI control performs the best with minimum overshoot.

Simulation of electro-mechanical friction clutch control using proportional derivative plus conditional integral control scheme for automotive application

This paper explains simulation works carried out to evaluate the performance of proportional-integral-derivative-based (PID-based) controls in controlling the electro-mechanical friction clutch (EMFC) for engagement and disengagement. The EMFC model is developed in Matlab/Simulink comprising DC motor's model and power screw mechanism's model. Four controls; proportional-integral (PI), proportional-integral-derivative (PID), proportional (P) and proportional derivative (PD), are applied on the model using 6 mm as the set point for the power screw's position. Among them, PD control performs the best with 0% overshoot, 0.041 mm steady state error and about 1.3 seconds settling time. Next, the PD control is updated with a conditional integral controller (PDPCI), resulting in approximately zero steady state error and only 0.68% overshoot, while settling time stays at 1.3 seconds. Subsequently, both PD and PDPCI controls are simulated to achieve EMFC's full engagement and disengagement. The final results show that PDPCI control performs the best with minimum overshoot.

Investigation on modeling and simulation BLDC motor fed universal actuation system

This paper deals with mathematical modeling of Permanent magnet brushless DC (BLDC) motor in MATLAB-SIMULINK environment. Modeling of BLDC motor carried in transfer function, transfer equations and state space model to verify the performance as actuators. Mathematical switches to control electronic commutation of BLDC motor based on signals of Hall Effect position sensor using three-phase inverter drive. Performance of the simplified mathematical inverter fed BLDC motor under steady state and dynamic conditions analyzed. Due to the switching losses during PWM generation generates low ripple content in torque of BLDC motor which described and eliminated through state space model. Comparison made of proposed modeling of BLDC motor with motor parameters like back-EMF, stator current and speed of BLDC motor, proposed work suggests the state space modeling holds a superior method for design of BLDC motor during high dynamic load performance and operating ranges.

Speed Control of Motor Based on Improved Glowworm Swarm Optimization

To better regulate the speed of brushless DC motors, an improved algorithm based on the original Glowworm Swarm Optimization is proposed. The proposed algorithm solves the problems of poor robustness, slow convergence, and low accuracy exhibited by traditional PID controllers. When selecting the glowworm neighborhood set, an optimization scheme based on the growth and competition behavior of weeds is applied to a single glowworm to prevent falling into a local optimal solution. After the glowworm’s position is updated, the league selection operator is introduced to search for the global optimal solution. Combining the local search ability of the invasive weed optimization with the global search ability of the league selection operator enhances the robustness of the algorithm and also accelerates the convergence speed of the algorithm. The mathematical model of the brushless DC motor is established, the PID parameters are tuned and optimized using improved Glowworm Swarm Optimization algorithm, and the speed of the brushless DC motor is adjusted. In a Simulink environment, a double closed-loop speed control model was established to simulate the speed control of a brushless DC motor, and this simulation was compared with a traditional PID control. The simulation results show that the model based on the improved Glowworm Swarm Optimization algorithm has good robustness and a steady-state response speed for motor speed control.

Design of PI Speed Controller for 3-Ph Converter fed DC motor drive using Symmetrical Optimization

ABSTRACT This research paper focuses on the mathematical model of DC motor drive fed from the 3-Ph converter and the design of the PI speed controller for its speed control. To evaluate the gain coefficients of the PI speed controller, Symmetrical Optimum criteria are proposed. The proposed criterion is easier to understand than other advanced control methods. Using this criterion the gains of the PI controller are obtained by developing the mathematical model of the DC motor drive. This controller can be easily implemented for real-time applications of keeping motor speed at any desired set-point speed under varying operating conditions. The speed performance using the proposed method was compared with the S-curve method in MATLAB. The simulation results, with constant operating speed, indicate that the proposed criterion provides superior speed performance than the S-curve method. A similar speed response can be obtained with the selected PI gains for variable speeds. Finally, a comparative study has been done to highlight the proposed method benefits.

Comparison between model based and non-model based sensorless methods of brushed DC motor

This paper presents a comparison between sensorless techniques for estimating speed of brushed DC motor. These techniques can be classified into two groups: model based methods, non-model based methods. The model based methods use a dynamic model of DC motor, where a sliding mode observer, pseudo-sliding mode observer and observer with PI controller are presented. The non-model based methods use a ripple component of DC motor current, where the motor speed is estimated by applying a novel approach. This approach uses a discrete bandpass filter with a floating bandwidth to extract information about the motor speed from the measured motor current. The results obtained from the experimental verification indicate that the novel approach estimates the motor speed correctly in a wide range of speeds.

축소된 직류 전동기 모델을 사용한 PI 관측기 기반 위치 제어 시스템의 안정도 해석

축소된 직류 전동기 모델을 사용한 PI 관측기 기반 위치 제어 시스템의 안정도 해석

Design, Implementation & Performance Analysis of Solar Tracking System on Simulink Platform

This paper presents the idea of tracking framework which was executed on Simulink stage. The variety in current and voltage for static and tracking SPV power plant are appeared in this paper. The relative study at various situating of panel (static force plant) is additionally appeared in this paper. The entire model like sun tracking model, static SPV model, LDR sensor model, DC motor model additionally appeared in the paper. The primary goal of this paper is to break down the outcomes concerning static force plant. The tiltaion edges are 30°, 60° and 90° static force plants. The simulation results and the impact of tiltation point are additionally introduced in this paper. In the closing comment, the improved effectiveness because of tracking method is appeared.

Iterative Learning Control for a Repetitive 2D Process

To control the systems which operate in a repetitive mode is known to be a difficult task. For example, systems like robotic manipulators are used for doing the repetitive assigned task. This can be overcome by the iterative learning control (ILC) method. In this article, the DC motor model is discussed for controlling the speed of the motor by the design of an ILC algorithm, and its performance is compared with the conventional PID algorithm. The ILC algorithm is implemented for the minimum and non-minimum phase systems. The resulting response, absolute and integral absolute errors are plotted. The Z-N tuning method is used to implement PID control. The performance of the DC motor has been evaluated by comparing the Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE) with the conventional PID controller.

Hard Dead Zone and Friction Modeling and Identification of a Permanent Magnet DC Motor Non-Linear Model

The identification of a permanent magnet DC motor model including non-linearities dead zone, Coulomb friction, and viscous friction, is presented. The dead zone considered here is the so call "hard" dead zone, whereas the friction force is modeled in two different ways: first, considering the value of viscous coefficient friction as a constant and second, approximating viscous coefficient by a polynomial depending on motors rotor velocity. The polynomial representation of the viscous friction value allows it to be adjusted automatically as a function of the speed of the system, as occurs in real systems. Therefore, a model capable of better representing the real motor behavior along a wide range of operation is obtained. The non-linear model is validated and compared using real-time data obtained from Quanser's direct current motor control trainer system, using the numerical tool Matlab®/Simulink™

Numerical and Experimental Approach to Characterize a BLDC Motor with Different Radial-gap to Improve Hemocompatibility Performance.

Left ventricular assist devices (LVADs) have increasingly been used clinically to treat heart failure patients. However, hemolysis, pump thrombosis, infection and bleeding still persist as major limitations of LVAD technology. Assessing LVAD hemocompatibility using a blood shear stress device (BSSD) has clear advantages, as the BSSD could provide a better experimental platform to develop reliable, quantifiable blood trauma assays to perform iterative testing of LVAD designs. In this study, a BSSD was proposed with short blood exposure time and no seals or contact bearings to reduce blood trauma caused by the test platform. Enlarged air-gap drive motor in BSSD is essential to avoid high shear stress; however, it would significantly reduce the motor torque, which may result in inadequate force to drive the entire system. In order to evaluate and optimize the drive motor air-gap to ensure adequate motor torque as well as acceptable range for blood exposure time and shear stress, a numerical brushless DC (BLDC) motor model was established using finite element method (FEM) in numerical simulation software COMSOL. The model was first validated by the experimental results. Then numerical model with different air-gap was evaluated on the torque and speed constant changes. In the end, two equations were generated based on the curves derived from the torque and speed constant calculations. Determining these relationships between motor performance and motor air-gap will facilitate the development of an appropriate BLDC motor size for the BSSD, considering the design limitations in our future work.

DC Motor Speed Control using Internal Model Controller Industrial Transformation Strategy

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

Development and control of a bicycle robot based on steering and pendulum balancing

This research focuses on the development of an electric bicycle robot which balances itself while moving at a constant forward speed. The bicycle robot is balanced by applying a pendulum mass moving together with heading steering to share the balancing load. The nonlinear dynamics model of a bicycle along with a pendulum is derived from the Euler-Lagrange equation of motion and nonholonomic constraints with respect to translation and rotation relative to the ground plane. This nonlinear model is then linearized around the upright position and combined with the DC motor model to obtain the completed linearized dynamics model. The robot's prototype is designed and built. The linear quadratic regulator (LQR) is implemented on the system to control its balance. The simulation results show that, by varying the control weighting matrix to increase the use of the pendulum's input, the system obtains better performance in both balancing and straight-line path tracking. In addition, the state weighting matrix can be varied to further improve the path tracking performance while still keeping the stability. Real experimental results are also in line with the simulation results.