Orbital Research Linear Adaptive Control - Manual

Orbital Research, Inc.
4415 Euclid Ave.
Cleveland, OH 44103
Contact: Frederick J. Lisy, Ph.D.
Telephone (216) 649-0399
E-mail [email protected]
www.orbitalresearch.com
Copyright 2003
Rev D RMK 12.2.2003
The Need for Adaptive Control
Occam's Razor dictates that the simplest control algorithm that
will produce the desired results should be used and, hence,
suggests the use of more conventional control theory that deals
predominantly with linear, constant coefficient systems. Linear
systems theory often provides a good approximation for systems
being regulated about a fixed operating point. Unfortunately,
linear control theory is not always sufficient, particularly in the
presence of large variations in system parameters or
disturbances. In addition, it not always possible to characterize a
system sufficiently to permit the complete design of a suitable
control system. The main reasons for using a nonlinear approach
such as adaptive control are: 1.) variations in plant dynamics, 2.)
variations in the characteristics of the disturbances, and 3.)
engineering efficiency.
Many systems are inherently nonlinear and linear approximations
are valid over only small regions of the systems operating
envelope. For instance, a robot arm’s inertial properties change
nonlinearly with the arm’s joint angles. Similarly, the
performance of actuators can vary widely under different
operating conditions such as changing temperature as well as
degrade over time due to wear or other environmental effects.
The use of an adaptive control scheme can greatly ameliorate the
deleterious effects that changing system parameters have on the
performance of the controller. While other techniques such as
robust high gain control can often accommodate a wide range of
system parameters, they do so at the cost of system
performance. Only adaptive control techniques permit
parameter variation while still allowing good control sensitivity
and responsiveness.
Disturbance accommodation is another important aspect of
control design. It is a straightforward process to compensate for
disturbances with given characteristics but the problem is far
more difficult if the disturbance patterns are unknown or are
, or changing with time. A classical example of a
nonstationary disturbance is wind load. As the weather
conditions change, not only does the magnitude and direction of
the wind change but the spectrum describing the wind load also
changes, both in mode and shape. A constant gain controller
designed to reject wind disturbances for a particular weather
condition is not going to be nearly as effective in other weather
conditions. Adaption provides a mechanism for retuning the
disturbance rejection properties of the control system in
response to changing environmental disturbances.
Finally, in many situations, the use of adaptive control is the
simplest choice. In many applications, due to system complexity
or inherent nonlinearity, it is either very difficult or impossible to
deduce appropriate system parameters from first principals. It
can therefore be advantageous to trade a more capable
controller design against the potentially more effort consuming
path of modeling, design and implementation of multiple control
systems.
nonstationary
I
n an increasingly competitive market place, today's systems require a high degree of flexibility,
robustness and performance. The need for ever faster, cheaper, and more capable systems is
driving a concomitant requirement for more robust, capable and flexible control systems. One
important class of modern control design techniques in this drive for better controllers is linear
adaptive control. In an adaptive controller, the controller itself can adapt its behavior to
accommodate changes in the system or the environment. Orbital Research, Inc. has developed a
family of linear adaptive controllers for a variety of applications, including a computationally
efficient predictive adaptive controller
Linear
Adaptive
Control
Flexible and robust
control enabling
today's applications
Adaptive Control provides a
mechanism for accomodating changes
in arm inertias and joint dynamics in robots.
Block diagram for the ORICA adaptve controller