Abstract
This study details online speed regulation of DC motor using PWM technique based on LabVIEW. A fuzzy logic controller is designed to change the pulse width of switching signal applied to the converter and thereby the voltage fed to the armature of the separately excited DC motor to regulate the speed. The proposed system is connected to the server computer using a Data Acquisition Card (DAQ) and the server computer is configured to access remote client computer using Web publishing tool in LabVIEW. Now the speed of the DC motor can be controlled by a remote client computer with Internet connection. Laboratory Virtual Instrument Engineering Workbench (LabVIEW) is a graphical programming environment for creating custom applications that interact with real-world data or signals in fields such as science and engineering. The proposed online control system has been implemented to control the speeds of two different motors and the experimental results are plotted. The conventional controllers need design objectives such as steady state and transient characteristics of the closed loop system to be specified. But the designed fuzzy logic controller overcomes the problems with uncertainties in the plant parameters. The proposed online control technique saves time and reduces the manpower.
Highlights
Motor speed regulation based on PID or model based feedback controllers will be inadequate
A fuzzy logic controller is designed to change the pulse width of switching signal applied to the converter and thereby the voltage fed to the armature of the separately excited DC motor to regulate the speed
The proposed system is connected to the server computer using a Data Acquisition Card (DAQ) and the server computer is configured to access remote client computer using Web publishing tool in Laboratory Virtual Instrument Engineering Workbench (LabVIEW)
Summary
Motor speed regulation based on PID or model based feedback controllers will be inadequate. If the DC motors are widely used in cranes, hoists, nonlinearities of the motor are known functions, conveyors, paper mills, textile mills and robotic adaptive tracking control methods with input-output manipulators Because they are reliable for an linearization can be used (Ibbini and Zakaria, 1996; extensive range of operating conditions and their Kim et al, 1997; Rigatos, 2009). The closed loop operation is simulated with the trained neural network to achieve the desired performance They have implemented PI controller in a neural network and a neuron controller has been designed to reduce the steady state error, overshoot and settling time. Jerome et al (2005) have proposed LabVIEW based intelligent controllers for speed regulation of electric motor They have developed an artificial neural network, fuzzy logic and neuro-fuzzy controllers to achieve accurate trajectory control of speed especially when DC drive and load dynamics are unknown. An FLC is designed and its performance is analyzed using different DC motors
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