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.

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.

A New Model Reference Adaptive Control Using Stacked Identifiers

2012 ◽  
Vol 488-489 ◽  
pp. 1767-1771
Author(s):  
Wei Der Chung ◽  
Xiao Hu ◽  
Woon Ki Na ◽  
Hsin Pei Chen ◽  
Yun Zhi Cheng ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Reference Model ◽  
Linear Time ◽  
Model Simulation ◽  
Design Method ◽  
Model Reference Adaptive Control ◽  
Primary Objective ◽  
Model Reference ◽  
Single Input Single Output ◽  
Model Reference Adaptive

Model reference adaptive control is a major design method for controlling plants with uncertain parameters. The primary objective of this paper is to develop a new design approach for the model reference adaptive control of a single-input single-output linear time-invariant plant. The proposed method, called the “Model reference adaptive control using stacked identifiers, “uses a stacked identifier structure that is new to the field of adaptive control. The goal is to make the output of the plant asymptotically track the output of the first identifier, and then driving the output of the first identifier to track that of the second identifier, and so forth, up to the q-th identifier where q is the relative degree of the plant. Lastly, the output of the q-th identifier is forced to converge to that of the reference model. Simulation results shown our paper provides a new adaptive scheme which may give a better transient performance. No state measurement of the plant is required in our method. Since the resulting control systems are nonlinear and time-varying, the stability analysis of the overall system plays a central role in developing the theory.

scholarly journals Nonlinear model reference adaptive control

1986 ◽  
Vol 28 (2) ◽  
pp. 147-157 ◽  
Author(s):  
J. M. Skowronski
Keyword(s):  
Adaptive Control ◽  
Nonlinear Model ◽  
Degrees Of Freedom ◽  
Control Program ◽  
Model Reference Adaptive Control ◽  
Design Technique ◽  
Model Reference ◽  
State Spaces ◽  
Adaptive Law ◽  
Model Reference Adaptive

AbstractThe known linear model reference adaptive control (MRAC) technique is extended to cover nonlinear and nonlinearizable systems (several equilibria, etc) and used to stabilize the system about a model. The method proposed applies the same Liapunov Design Technique but avoids the classical error equation. Instead it operates in the product of the state spaces of plant and model, aiming at convergence to a diagonal set. Control program, Liapunov functions and adaptive law are specified. The case is illustrated on a two-degrees of freedom robotic manipulator.

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