Skip to main content

PERFORMANCE COMPARISON OF TWO CONTROLLERS ON A NONLINEAR SYSTEM


International Journal of Chaos, Control, Modelling and Simulation (IJCCMS)
ISSN : 2319 - 5398 [Online] ; 2319 - 8990 [Print]

Article Title: PERFORMANCE COMPARISON OF TWO CONTROLLERS ON A NONLINEAR SYSTEM

Abstract
Various systems and instrumentation use auto tuning techniques in their operations. For example, audio processors, designed to control pitch in vocal and instrumental operations. The main aim of auto tuning is to conceal off-key errors, and allowing artists to perform genuinely despite slight deviation off-key. In this paper two Auto tuning control strategies are proposed. These are Proportional, Integral and Derivative (PID) control and Model Predictive Control (MPC). The PID and MPC controller's algorithms amalgamate the auto tuning method. These control strategies ascertains stability, effective and efficient performance on a nonlinear system. The paper test and compare the efficacy of each control strategy. This paper generously provides systematic tuning techniques for the PID controller than the MPC controller. Therefore in essence the PID has to give effective and efficient performance compared to the MPC. The PID depends mainly on three terms, the P () gain, I () gain and lastly D () gain for control each playing unique role while the MPC has more information used to predict and control a system.

KEYWORDS
Auto Tuning, Nonlinear system, Control law, PID & MPC



Comments

Popular posts from this blog

Comparison of Support Vector Machines and Deep Learning for Plant Classification in Smart Agriculture Applications

Comparison of Support Vector Machines and Deep Learning for Plant Classification in Smart Agriculture Applications Authors Esmael Hamuda 1, Ashkan Parsi 2, Martin Glavin 2 and Edward Jones 2, 1 Elmergib University, Libya, 2 University of Galway, Ireland Abstract In this paper, we investigate the use of deep learning approaches for plant classification (cauliflower and weeds) in smart agriculture applications. To perform this, five approaches were considered, two based on well-known deep learning architectures (AlexNet and GoogleNet), and three based on Support Vector Machine (SVM) classifiers with different feature sets (Bag of Words in L*a*b colour space, Bag of Words in HSV colour space, Bag of Words of Speeded-up Robust Features (SURF)). Two types of datasets were used in this study: one without Data Augmentation and the second one with Data Augmentation. Each algorithm's performance was tested with one data set similar to the training data, and a second data set acquired under ...

Submit your Research Article - International Journal of Chaos, Control, Modelling and Simulation (IJCCMS)

Submit your Research Article!! International Journal of Chaos, Control, Modelling and Simulation (IJCCMS) ISSN :  2319 - 5398 [Online] ; 2319 - 8990 [Print] Webpage URL:  https://airccse.org/journal/ijccms/index.html Submission URL:  http://coneco2009.com/submissions/imagination/home.html Here's where you can reach us :  ijccmsjournal@yahoo.com or ijccms@aircconline.com

6th International Conference of Control Theory and Computer Modelling (CTCM 2020)

October 24 ~ 25, 2020, Dubai, UAE https://csen2020.org/ctcm/index.html Submission Deadline: July 26, 2020 Contact us: Here's where you can reach us: ctcm@csen2020.org (or) ctcmconference@yahoo.com Submission Link: https://csen2020.org/submission/index.php