Refine your search
Collections
Co-Authors
Journals
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Mandloi, Aditya
- Performance Analysis of Discrete and Fuzzy PID Controller
Abstract Views :186 |
PDF Views:3
In a control system, there are two important parts one is controller and other is plant. Here Discrete PID and fuzzy PID is design to control DC motor. DC motors are use in several applications because of high torque, low volume and high efficiency.
By an approximation called fuzzy smoothness we made nine rules which help us to achieve zero overshoot i.e., output response is not crossing reference value of time, which make fuzzy PID differ and superior then discrete PID. In fuzzy PID, Rise time is 3.655 and settling time is 7.345 which are better than Discrete PID controller.
Authors
Affiliations
1 Elec. & Comm. Engg., Medicaps Institute of Technology and Management, Indore (M.P.), IN
1 Elec. & Comm. Engg., Medicaps Institute of Technology and Management, Indore (M.P.), IN
Source
Fuzzy Systems, Vol 6, No 3 (2014), Pagination: 65-67Abstract
More than 95% of dynamic controllers are of PID variety. PID is used in servo-motor/dc motor/temperature control system, robotics, power electronics etc. conventional PID has some limitations to overcome from it discrete PID is come in the circumstances, then for advance improvement fuzzy PID is introduced. The fuzzy PID controller is one of the vital controller in electronics control module in automotive application in which vagueness and ambiguity is exists. In this fuzzy PID system is designed and compared with discrete PID system. There are three main parameter in control system i.e., peak overshoot, rise time and settling time which we are comparing in this project. First the discrete PID then Fuzzy PID control system is design in MATLAB Simulink which is developed to reduce the Peak Overshoot in discrete PID and zero overshoot in Fuzzy PID by focusing only on significant rules and ignoring those which are unrelated to the condition for better performance. MATLAB is used to design PID controller to calculate and plot the time response of the control system and Simulink to generate a set of coefficients.In a control system, there are two important parts one is controller and other is plant. Here Discrete PID and fuzzy PID is design to control DC motor. DC motors are use in several applications because of high torque, low volume and high efficiency.
By an approximation called fuzzy smoothness we made nine rules which help us to achieve zero overshoot i.e., output response is not crossing reference value of time, which make fuzzy PID differ and superior then discrete PID. In fuzzy PID, Rise time is 3.655 and settling time is 7.345 which are better than Discrete PID controller.
