PID Controller Design and Tuning Methods for Industrial Automation

TABLE OF CONTENTS
1. INTRODUCTION...............................................................................................................................2
Basic Overview.......................................................................................................................................2
2. AIMS AND OBJECTIVES.................................................................................................................7
3. PROBLEM STATEMENT..................................................................................................................7
4. DESIGN METHODOLOGY...............................................................................................................7
5. LOOP TUNING METHODS............................................................................................................11
Manual tuning Method..........................................................................................................................12
Ziegler-Nichols method.........................................................................................................................12
Cohen-Coon Method.............................................................................................................................14
6. DESIGN, SIMULATION AND MATLAB IMPLEMENTATION...................................................16
7. RESULTS AND OBSERVATION...................................................................................................18
8. DISCUSSION...................................................................................................................................21
PLC for implementation- flexibility, availability, and cost....................................................................22
Safety critical shutdown system............................................................................................................24
REFERENCES..........................................................................................................................................26
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1. INTRODUCTION
Basic Overview
Industrial automation involves the technology in which a procedure or the process is
accomplished with little or no human interference or assistance. Industrial automation has cost
benefits. The industrial automation has to do with the regulation and control of individual unit
operations alongside accompanied units. The integration of the units and cascaded control leads
into control of the larger production systems. The regulatory control maintains the process
enactment at a defined level or within a set tolerance band of a given level. Index of efficiency
may be computed based on several output variables. For a process to be controlled there must be
an error so as to initiate a control action.
Feed forward control antedates the effect of turbulences that will distort the process by
using a sensor and a compensator for them before they affect the course. Disturbances need to be
established using mathematical models in the system [1]. It is quite difficult to completely
compensate for the disorder due to disparities, deficiencies in the mathematical model and
imperfections in the control actions. The monitoring control and feed forward regulator are used
to design the control processes. Steady-state optimization is implemented in systems where the
index of performance is well-defined and there is a definite relationship between the process
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variables and IP. Mathematical models are used to optimize the index of performance based on
system parameter values.
The most commonly used controller in industrial applications is the proportional-integral-
derivative controller. The PID controller computes the error value which results from the
alteration between the anticipated output or yield and the measured process variable. A feedback
loop is used to perform the computation. The feedback loop mainly contains a sensor which
collects data from the output and relays it to the error computation point. The controller has three
segments namely the proportional, the integral, the derivative. The proportional term relies on
the current errors, the integral component relies on the accumulation of the past errors, and the
derivative component relies on the prediction of the future errors. The impact of these three
components brings about change when implemented in the regulating valve before the mixing
process commences. It is quite a crucial component in industrial implementations and the
controller can deliver control action intended for specific process requirements [2].
Designers use the manipulated variable to determine the PID control scheme. The
controllers are manufactured or fabricated in three different components such as the proportional,
integral, and derivative modes. They could be interactive algorithms, non-Interactive algorithms
and parallel algorithms such that,
(i) The interactive algorithm is defined as,
U ( t ) =k c [ e ( t ) + 1
Ti
∫
0
t
e ( τ ) dτ ] x [ 1+ Td
d
dt e ( t ) ]
It is implemented in a system such that,
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(ii) The non-interactive algorithm is defined as,
U ( t )=k c [e ( t ) + 1
Ti
∫
0
t
e ( τ ) dτ +T d
d
dt e ( t ) ]
It is implemented in a process plant system as,
(iii) The parallel algorithm is defined as,
U ( t )=k p e ( t ) +k i∫
o
t
e (τ )dτ + Kd
d
dt e (t)
It is implemented in a process plant system as,
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Therefore, it is possible to build a PID controller based on all three components working
together. There are several other controllers, for instance, the proportional (P) controllers,
proportional-integral (PI) controllers, proportional-derivative (PD) controllers, and the
proportional-integral-derivative (PID) controllers. The P controller is implemented in first order
systems. Its main function is to reduce the steady state error of the system. An increase in the
gain parameter leads to the decrease in the steady state error up to a certain level where further
increase in the gain parameter causes the system output to oscillate [3]. Unfortunately, it fails to
eliminate the steady state error and it is observed to amplify the process noise in the system. The
PI controller solves the P controller’s drawback as it eliminates the steady state error and the
oscillations as a result of the high proportional gain constant. Unfortunately, this controller is
observed to have a poor performance when it comes to the speed of response and the overall
stability of the system. Further, it is unable to decrease the rise time. The PD controller increases
the system stability while improving the controlling nature of the system with the aim of
predicting future error of the system response.
The PID controller combines all the benefits of the other controllers such as the
elimination of steady state error and oscillations in the output, ensures system stability while
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