Some issues on the practical use of recursive least squares identification in self-tuning control

1991 ◽  
Vol 53 (5) ◽  
pp. 1021-1033 ◽  
Author(s):  
O. P. MALIK ◽  
G. S. HOPE ◽  
S. J. CHENG
Keyword(s):  
Least Squares ◽  
Recursive Least Squares ◽  
Self Tuning

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

1998 ◽  
Vol 212 (6) ◽  
pp. 437-448 ◽  
Author(s):  
K Warwick ◽  
Y-H Kang
Keyword(s):  
Least Squares ◽  
Adaptive Controller ◽  
Recursive Least Squares ◽  
Industrial Processes ◽  
Industrial Plant ◽  
Parameter Estimator ◽  
Proportional Integral ◽  
Control Scheme ◽  
Self Tuning ◽  
Real Plant

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Identification and Control of Nonlinear Laboratory Model Amira DR 300

2014 ◽  
Vol 611 ◽  
pp. 284-293
Author(s):  
Petr Navrátil
Keyword(s):  
Least Squares ◽  
Recursive Least Squares ◽  
Laboratory Model ◽  
Adaptive Controllers ◽  
Real Model ◽  
Model Control ◽  
Simulation Testing ◽  
Self Tuning ◽  
Adaptive Forgetting ◽  
And Control

This article deals with identification and a control design of nonlinear laboratory model Amira DR 300 in a real time. It mentions a mathematical description of the model, its static and dynamical characteristics. Using an experimental method of identification a model has been created, which is suitable for the purpose of simulation testing of non-adaptive as well as adaptive controllers. These were tested as simple adaptive, i.e. non-adaptive controllers, namely in both simulation ways and at a real model control. For the purpose of a non-adaptive control, system parameters were determined by off-line method of the least squares. In an identification part of self-tuning controllers a method of recursive least squares with directional adaptive forgetting factor has been used.

scholarly journals Identification by Recursive Least Squares with Kalman Filter (RLS-KF) Applied to a Robotic Manipulator

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Darielson A. Souza ◽  
Josias G. Batista ◽  
Felipe J. S. Vasconcelos ◽  
Laurinda L. N. Dos Reis ◽  
Gabriel F. Machado ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Least Squares ◽  
Robotic Manipulator ◽  
Recursive Least Squares
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