with x = [x1 x˙ 1]T and w = g is considered as a disturbance.
The objective of this paper is to design an anti-windup
adaptive PID control of the magnetic levitation system which
has the output y(t) regulates a set point r.
B. Error System with Internal Model Filter
In order to achieve the control objective, we first introduce
an internal model filter.
u(t) = GIM(s)[ua(t)] =
s +
s
[ua(t)] , (4)
where ua(t) is a designed control input.
Defining an output error by e(t) = y(t)−ym, the obtained
error system form the input ua(t) to the error e(t) can be
expressed by the following form:
˙e(t) = Aee(t) + beua(t) + b(t)
˙ (t) = −(t) + cT e(t)
e(t) = [1 0]e(t)
(5)
Where e(t) = [e(t), e˙(t)]T , and Ae, be, b and c are
appropriate matrix and vectors.
It is noted that the error system (5) with the internal
model filter can be expressed as 3rd order system with a
stable first order zero dynamics in which the effects from
the disturbance has been eliminated and has the following
transfer function.
G
p2(s) = G
p1(s)GIM(s) =
b(s + )
s2(s + )
(6)
In the following section, we first consider to design an
ASPR based adaptive PID control system.
III. ASPR AUGMENTED SYSTEM WITH A PFC
In order to design an ASPR based adaptive PID control
system, the controlled system must be ASPR. Since the error
system (5) is not ASPR, we consider introducing a PFC in
parallel with the error system (5). The PFC is designed so
as to render the augmented controlled system with a PFC in
parallel ASPR.
A. Model-based PFC Design
The model-based PFC design scheme has been provided
as one of the simple PFC design schemes [6], [7]. In this
scheme, the PFC GPFC(s) can be designed using the system
approximated model as follows:
GPFC(s) = GASPR(s) − G
p2(s) (7)
where GASPR(s) is a given desired ASPR model and G
p2(s)
is an approximated model of the controlled system.
In the considering magnetic levitation system, the approximated
model is given in (6) . Taking this in consideration,
we design an ASPR model as a form of
GASPR(s) =
k(s + h0)
s2
(8)