Sponsor
Portland State University. Department of Electrical and Computer Engineering
First Advisor
Garrison Greenwood
Date of Publication
Summer 1-1-2012
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Electrical and Computer Engineering
Department
Electrical and Computer Engineering
Language
English
Subjects
PID controllers -- Design and construction, Nonlinear systems -- Design and construction, Fuzzy logic, Evolutionary programming (Computer science)
DOI
10.15760/etd.512
Physical Description
1 online resource (v, 57 p.) : ill. (chiefly col.)
Abstract
This research presents a solution to the problem of tuning a PID controller for a nonlinear system. Many systems in industrial applications use a PID controller to control a plant or the process. Conventional PID controllers work in linear systems but are less effective when the plant or the process is nonlinear because PID controllers cannot adapt the gain parameters as needed. In this research we design a Nonlinear PID (NPID) controller using a fuzzy logic system based on the Mamdani type Fuzzy Inference System to control three different DC motor systems. This fuzzy system is responsible for adapting the gain parameters of a conventional PID controller. This fuzzy system's rule base was heuristically evolved using an Evolutionary Algorithm (Differential Evolution). Our results show that a NPID controller can restore a moderately or a heavily under-damped DC motor system under consideration to a desired behavior (slightly under-damped).
Rights
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Persistent Identifier
http://archives.pdx.edu/ds/psu/8479
Recommended Citation
Chopra, Shubham, "Evolved Design of a Nonlinear Proportional Integral Derivative (NPID) Controller" (2012). Dissertations and Theses. Paper 512.
https://doi.org/10.15760/etd.512
Included in
Other Computer Sciences Commons, Other Electrical and Computer Engineering Commons, Theory and Algorithms Commons