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Abstract-- The paper is mainly concerned on Liquid level
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control systems which are commonly used in many process
control applications to control, for example, the level of liquid in
a tank. Liquid enters the tank using a pump, and after some
processing within the tank the liquid leaves from the bottom of
the tank. The requirement in this system is to control the rate of
liquid delivered by the pump so that the level of liquid within
the tank is at the desired set point. IMC tuned PID algorithm is
implemented in MICROC programming language and it is
loaded into the PIC microcontroller. The controller generate the
output according to the error signal and derives the system
towered the zero error. It is also interfaced with PC through
MAX232 and DB9 connector for system identification and the
observation of output of the system. 8843
Index Terms—ADC,DAC, IMC, MICROC, PIC, PID
I. INTRODUCTION
The Internal Model Control (IMC) philosophy relies on the
Internal Model Principle, which states that control can be
achieved only if the control system encapsulates, either
implicitly or explicitly, some representation of the process
to be controlled. In particular, if the control scheme has
been developed based on an exact model of the process,
then perfect control is theoretically possible. In practice,
however, process-model mismatch is common; the process
model may not be invertible and the system is often
affected by unknown disturbances. Thus the above open
loop control arrangement will not be able to maintain
output at setpoint. Nevertheless, it forms the basis for the
development of a control strategy that has the potential to
achieve perfect control. This strategy, known as Internal
Model Control (IMC) has the general structure depicted in
Fig. 1
IMC-based PID Controller
The internal model control (IMC) algorithm is based on
the fact that an accurate model of the process can lead to the
design of a robust controller both in terms of stability and
performance [1]. The basic IMC structure is shown in Figure
1 and the controller representation for a step perturbation is
described by (1). ) (s Gmm
is the inverse minimum phase part of the process
model and
) (s Gf
is a nth
order low pass filter
n
s ) 1 ( 1 λ
. The filter’s
order is selected so that
) (s Gq
is semi-proper and λ is a
tuning parameter that affects the speed of the closed loop
system and its robustness [2]. However, there is equivalence between the classical
feedback and the IMC control structure, allowing the
transformation of an IMC controller to the form of the well-
known PID algorithm.
The resulted controller is called IMC-based PID controller
and has the usual PID form (3).
IMC-based PID tuning advantage is the estimation of a
single parameter λ instead of two (concerning the IMC-based
PI controller) or three (concerning the IMC-based PID
controller). The PID parameters are then computed based on
that parameter [1]. Though for the case of a FOPDT process
model, the delay time should be approximated first by a zero-
order Padé (usually) approximation [3]. However, the IMC-
based PID tuning method can be summarized according to
the following Table 1 [2]. process
Recent [4-6] simulation studies shows that IMC tuned
PID parameter provides better performance than S-F
based or ZN based tuning methods. In this paper we
design a practical set up for implementation and
verification of digital IMC tuned PID algorithm on PIC
microcontroller.
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