Model reference adaptive control via the minimisation of output error and weighting control input

1989 ◽  
Vol 136 (5) ◽  
pp. 231 ◽  
Author(s):  
Chih-Lyang Hwang ◽  
Bor-Sen Chen
Keyword(s):  
Adaptive Control ◽  
Model Reference Adaptive Control ◽  
Control Input ◽  
Model Reference ◽  
Output Error ◽  
Model Reference Adaptive

Model Reference Adaptive Control of Feed Force in Turning

1986 ◽  
Vol 108 (3) ◽  
pp. 215-222 ◽  
Author(s):  
L. K. Daneshmend ◽  
H. A. Pak
Keyword(s):  
Adaptive Control ◽  
Model Reference Adaptive Control ◽  
Numerical Control ◽  
Control Input ◽  
Design Technique ◽  
Model Reference ◽  
Single Input Single Output ◽  
Single Output ◽  
Feed Force ◽  
Model Reference Adaptive

This paper applies the discrete-time single-input/single-output Model Reference Adaptive Control (MRAC) design technique of Landau and Lozano to the problem of regulating feed force on a lathe under varying cutting conditions. A first-order model is used to represent the relationship between feed force and the control input (feedrate). The MRAC scheme is implemented on a multi-microprocessor based computer-numerical-control system. Results of applying various algorithms derived from the MRAC design technique are presented.

Model Reference Adaptive Control with Output Error Feedback

1997 ◽  
Vol 30 (11) ◽  
pp. 335-340
Author(s):  
Masahiro Oya ◽  
Toshihiro Kobayashi ◽  
Shinichi Sagara
Keyword(s):  
Adaptive Control ◽  
Model Reference Adaptive Control ◽  
Error Feedback ◽  
Model Reference ◽  
Output Error ◽  
Model Reference Adaptive

Experimental evaluation of a model reference adaptive control for a hydraulic robot: a case study

Robotica ◽  
2003 ◽  
Vol 21 (1) ◽  
pp. 71-78 ◽  
Author(s):  
Ali Kireçci ◽  
Mehmet Topalbekiroglu ◽  
İlyas Eker
Keyword(s):  
Adaptive Control ◽  
Model Reference Adaptive Control ◽  
Computational Time ◽  
Position Tracking ◽  
Control Input ◽  
Model Reference ◽  
Solution Methods ◽  
The Stability ◽  
Classical Control ◽  
Model Reference Adaptive

This paper presents the implementation of an explicit model reference adaptive control (MRAC) for position tracking of a dynamically unknown robot. An auto regressive exogenous (ARX) model is chosen to define the plant model and the control input is optimised in a H2 norm to reduce computational time and to simplify the algorithm. The theory of MRAC falls into a description of the various forms of controllers and parameter estimation techniques, therefore, applications may require very complicated solution methods depending on the selected laws. However, in this study, the proposed MRAC shows that applications may be as easy as classical control methods, such as PID, by guaranteeing the stability and achieving the convergency of the plant parameters. Despite the selected simple control model, simple optimisation method and drawbacks of the robot the experimental results show that MRAC provides an excellent position tracking compared with conventional control (PID). Many experimental implementations have been done on the robot and one of them is included in the paper.

Sign in / Sign up

Export Citation Format

Share Document