DC Motor Control System Research Articles

Simulation and Design of Double Close-Loop DC Motor Control System Based on Matlab

In this paper, based on the principle of the speed and current double closed loop DC regulating system and the requirement of the static and dynamic performance, we calculate time constant of the regulator, select the structure of the regulator to calculate related parameter and then correct its parameters, and model system and simulation by using Simulink, analysis waveform and debug to find out the optimal parameters of the system regulator to guide the actual system design.

Optimization Design of Permanent-Magnetism Brushless DC Motor Governing System Based on Artificial Fish Swarm Algorithm

The optimal design approach of the PID controller was proposed in this paper, based on Artificial Fish Swarm Algorithm (AFSA) for the matter of the optimization of the brushless DC motor controller. In the experiment, through the analysis of the basic principles of artificial fish swarm algorithm, appropriate performance index was selected as fitness function, specific design procedures were given to optimize parameters of PID controller, The experimental results indicate that: Artificial Fish Swarm Algorithm optimized PID controller enables the brushless DC motor speed control system response faster, small overshoot, effectively improve the dynamic performance of a brushless DC motor control system.

Design of Brushless DC Motor Control System Based on ARM

In order to achieve the precise control of brushless DC motor better, the system utilizes powerful motion control performance and rich on-chip peripheral resources of 32-bit microprocessor LM3S811. combining with Pulse Width Modulation tecnology and Proportion Integration Differentiation closed-loop control algorithm based on feedback, designs a stable and efficient three-phase full-bridge inverter driver circuit and achieves a reliable control system of brushless DC motor based on ARM Cortex-M3 microprocessor platform. Low power and low cost performance will make the system has good market prospects and application value.

Application of Fuzzy PI Control to Speed Control System of Brushless DC Motor

Basing on analysis the principle and mathematical model of the brushless DC motor, the paper proposes a control model on the basis of speed loop and current loop, fuzzy PI control model is adopted in the speed loop, and traditional PID control model is used in the current loop. It is showed that when the load or parameters vary, comparing to traditional PID control model, the fuzzy PI control model gets less fluctuation and better robustness.

DFT 기반의 시스템 모델링을 이용한 DC Motor의 위치제어

This study presents a new method of system modeling by using the Discrete Fourier Transform for the position control system of DC Motor. And the proposed method is similar to the method of System Identification by analysis of correlation of the measured input-output data. The measured output signals are transformed to the frequency domain using DFT. The Fourier Spectrum of the transformed signals is used for knowing to the feature of having an important effect on the system. And transfer function of the second order system is estimated by the dominant parameter which is computed in the magnitude and the phase of Fourier spectrum of the transformed signals. In addition, the output signal includes the unique feature of system. So, although the basic parameter of the system is unknown for us, the proposed method has an advantage to system modeling. And the controller is easily designed by the estimated transfer function. Thus, in this paper, the proposed method is applied to the system modeling for the position control system of DC Motor and the PD-controller is designed by the estimated model. And the efficiency and the reliability of the proposed method are verified by the experimental result.

DC Brushless Motor Control Design and Preliminary Testing for Independent 4-Wheel Drive Rev-11 Robotic Platform

This paper discusses the design of control system for brushless DC motor using microcontroller ATMega 16 that will be applied to an independent 4-wheel drive Mobile Robot LIPI version 2 (REV-11). The control system consists of two parts which are brushless DC motor control module and supervisory control module that coordinates the desired command to the motor control module. To control the REV-11 platform, supervisory control transmit the reference data of speed and direction of motor to control the speed and direction of each actuator on the platform REV-11. From the test results it is concluded that the designed control system work properly to coordinate and control the speed and direction of motion of the actuator motor REV-11 platform.

106 安価に製作できる簡易型DCモータ制御学習教材の開発(GS 機械システムの制御と教育)

106 安価に製作できる簡易型DCモータ制御学習教材の開発(GS 機械システムの制御と教育)

Dynamic Response of the Double Loop DC Motor Control System with the Different Moment of Inertia

According to the relation of inertia moment and electromechanical time constant, dynamic structure and inertia moment of double loop DC motor control system is proposed. The effect of the moment of inertia on the dynamic response process of the double-loop DC control system is analyzed. In addition, the mathematical relation of the inertia moment and the rotation acceleration for the double-loop DC control system is discussed. Lastly, the effectiveness of the mathematical relation is verified through the experiment of the actual system.

Design and Simulation of Brushless DC Motor Control System Based on DSP

Based on the principle of sensorless control of brushless DC motor (BLDC) and combining the characteristics of TMS320LF2407A, this paper mainly researched on the key techniques of position detection and starting for sensorless BLDC. And put forward a sensorless BLDC control system, which combined back-EMF and pre-position start mode. The simulation has shown that the control system meets the requirements of stability and rapidity, and it is able to control motor precisely.

Design of Control System of DC Motor Based on Fusion FPGA

Along with the development of microelectronic process, it is possible to integrate a big system in one chip. A new way to implement system on a chip is provided by the advent of FPGA. Based on Verilog HDL and the Actel Fusion AFS600 FPGA chip, the speed closed-loop control system of DC motor was designed by using options of combining the top-down thinking and the bottom-up method. PID control algorithm, encoder signal processing and PWM waveform generation etc were realized by the system. The results show that the system structure is simplified and the stability and reliability are improved. A solution of system on a chip is realized to some extent. It has extensive application value in engineering practice.

Adaptive Dynamic RBF Fuzzy Neural Controller Design with a Constructive Learning

Radial basis function (RBF) network can be viewed as a fuzzy rule base with specified membership functions and fuzzy inference operations. However, there is a trade-off between the approximation performance of RBF network and the number of hidden neurons. To tackle this problem, this paper proposes a dynamic RBF (DRBF) network with a constructive learning. This DRBF network not only can create the new hidden neurons, but also can prune the insignificant hidden neurons. Then, an adaptive dynamic RBF fuzzy neural control (ADRFNC) system, including a neural controller and a saturation compensator, is developed. The neural controller uses a DRBF network to on-line mimic an ideal controller and the saturation compensator is designed to dispel the approximation error introduced by the neural controller. Finally, the proposed ADRFNC system is applied to a chaotic circuit and a DC motor control system. Simulation and experimental results show the proposed ADRFNC system can achieve a favorable tracking performance when the controller’s parameters have been learned and the network structure has been constructed by the proposed learning algorithm.

Design of DC Motor Control System Based on Clonal Selection Algorithm

According to the multivariate, strong coupling and nonlinearity of the DC motor speed control system, and the traditional PID control is difficult to achieve the higher speed performance. Combining the clonal selection algorithm (CSA) with the traditional PID control, a kind of intelligent PID control system was designed. The controller realizes the real-time and online adjustment of PID parameters, thus, the dynamic and static performance and robustness of the DC motor control system was improved. The simulation experiment was processed based on MATLAB environment. Simulation results show that this intelligent PID controller achieves better performance than the traditional PID controller.

A High-Precision Control System of DC Motor Based On DSP

A new scheme of high-precision DC motor control system based on DSP-TMS320F28335 as a core control chip is proposed in this paper. The scheme adopts PID control and Active Control strategy. The tests result greatly meets the needs of rotating and reversing performance in the reversible control system. The scheme, using a simple structure, is feasible and reliable, which shows a great engineering value in the field of high-precision control.

Design of the Closed Loop Speed Control System for DC Motor

This article introduces the speed control principle of DC motor, expatiates on the speed control system taking PIC16F877 SCM as the main control component, utilizes the characters of catching module, comparing module and analog-to-digital conversion module in PIC16F877 SCM to be the trigger circuit, and gives the program flow chart. The system has many advantages including simple structure, synchronization with the main circuit, stable shifting phase and enough shifting phase range, the control angle of 10000 steps, stepless smooth control of motor, steep pulse front edge, enough amplitude value, setting pulse width, good stability and anti-jamming, and cheap cost, and this speed control system with good practical values can be realized easily.

Modelling and simulation of control system for brushless DC motor

Based on the mathematical model of the brushless DC motor (BLDCM), using a novel method of modularisation design for modelling and simulation, the isolated functional blocks, for instance, BLDCM body block, speed PI controller block, current hysteresis controller block, current reference block, inverter block and commutation logic block, have been modelled in Matlab/Simulink. By the organic combination of these blocks, the simulation model of control system for BLDCM has been established. Additionally, some simulation works such as current waveform, back EMF waveform, torque curve and rotor speed curve have been done in this study. The simulation results indicate that the established model based on the new method proposed in this study has a good response to the rotor speed and torque and possesses quick simulation pace, which offers foundation for the design of actual motor control system.

LabVIEW의 모델기반 제어기 설계와 Compact RIO를 이용한 직류전동기 구동 시스템

This paper presents a controller implementation using model based controller design programs-System Identification Toolkit, Control Design Toolkit, Simulation module. This method is easier and simpler than conventional controller design method. To implement speed control system of DC motor, a CompactRIO, Real-Time(RT) cntroller provided by NI(National Instruments), is used as hardware equipment. Firstly transfer function of DC motor drive system, which was a control target plant, can be acquired through System Identification Toolkit by using test input signal applied to motor and output signal from motor. And designing of pole-zero compensator satisfying desired control response performance through Control Design Toolkit, designed speed control response can be tested through Simulation Module. Finally LabVIEW program is converted to real-time program and downloaded to CompactRIO real-time controller Through experimental results to real DC motor drive system, designed speed control response is compared to simulation results.

Hardware/Software Co-design Approach for an ADALINE Based Adaptive Control System

In this paper, we report some results on hard- ware and software co-design of an adaptive linear neuron (ADALINE) based control system. A discrete-time Pro- portional-Integral-Derivative (PID) controller is designed based on the mathematical model of the plant. The pa- rameters of the plant model are identified on-line by an ADALINE neural network. In order to efficiently and economically implement the designed control system, a Field Programmable Gate Array (FPGA) chip is em- ployed to process the measured data and generate control signals. Moreover, a microprocessor is exploited to per- form the core computation of the ADALINE algorithm. Throughout the paper, we design and test the control system for a permanent magnetic DC motor. Our ex- periment results demonstrate the effectiveness of the pro- posed approach. It is worth noting that the experimental bed in the present paper can also be used as a low-cost general prototype to satisfactorily test adaptive control systems, owing to the benefit of software and hardware co-design.

Neurofuzzy Modelling and Pattern Matching for Online Fault Detection and Isolation of Nonlinear DC Motors

An online fault detection and isolation scheme for nonlinear systems based on neurofuzzy modelling and pattern matching is developed in this paper. The system is first modelled offline by a neurofuzzy network using data obtained under normal operating conditions. Another neurofuzzy network is then used to model the residual, which is the difference between the output of the system and that from the neurofuzzy network. For online fault monitoring, it is necessary to construct first a fault database that contains fuzzy rules for all possible faults in the system. Recursive least squares algorithm is used to train the network online, from which the IF-THEN rules are extracted. Faults are isolated online by comparing these fuzzy rules with those in the fault database using a nearest neighbour classifier. A simulation example involving a nonlinear DC motor control system is used to demonstrate the implementation and performance of the proposed FDI scheme.

DC motor speed control methods using MATLAB/Simulink and their integration into undergraduate electric machinery courses

AbstractThis paper describes the MATLAB/Simulink realization of the DC motor speed control methods, namely field resistance, armature voltage and armature resistance control methods, and feedback control system for DC motor drives. These simulation models are developed as a part of a software laboratory to support and enhance undergraduate electric machinery courses at Nigde University, Nigde, Turkey. © 2007 Wiley Periodicals, Inc. Comput Appl Eng Educ 15: 347–354, 2007; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20151

Implementation of Low Cost and Advanced Slotless Brushless DC Motor Drive Using PLL Algorithm

In this article, in order to enhance the performance of Hall-ICs, a position signal synthesize control algorithm is developed. Also, considering diagnosis of permanent magnet brushless DC (PM BLDC) motor control and safety operation or system protection in case of having trouble and fault in one of Hall-ICs during operation, the developed two Hall-IC control scheme is applied. With the position signal of phase lock loop (PLL) control algorithm and the remainder scheme, one can operate the slotless PM BLDC motor in high performance.