SIMATIC PCS 7 Process Control System - Siemens

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Engineering system
ES software
Standard engineering software
I&C libraries
Examples of editable OS standard displays (faceplates) from the PCS 7
library
Preconfigured and tested blocks, faceplates and symbols are
organized in I&C libraries and form the basic elements for the
graphic configuration of automation solutions. The use of these
library elements plays a major role in minimizing the engineering
input and project costs.
The comprehensive range of blocks can be categorized as follows:
• Simple logic and driver blocks
• Technological blocks with integral operation and signaling
functions such as PID controllers, motors or valves
• Blocks for integration of PROFIBUS field devices in accordance
with PROFIBUS PA profile 3.0 (including standardized
evaluation of the process value status)
• Blocks with more advanced control algorithms for Advanced
Process Control (APC) functions
Advanced Process Control (APC) functions
The APC functions concentrated in separate blocks expand the
PID-based control functions of SIMATIC PCS 7 by more advanced
control algorithms, e.g.:
• Model-based multi-variable controller
The use of a multi-variable controller is recommendable for complex
processes where several variables which are mutually dependent
have to be controlled. Separate control of the individual
variables, e.g. using PID controllers, has the disadvantages that
interactions result in different effects on the respective variables.
The model-based ModPreCon multi-variable controller integrated
in SIMATIC PCS 7 separately analyzes the response of up
to four mutually dependent variables over a longer period of
time. A parameter matrix is calculated from the results, and used
by the ModPreCon for optimum control of the variables.
Note:
The ModPreCon makes great demands on memory and processing time
of the designated automation system. For that reason, please check the
resources of the designated automation system before use. We recommend
the use of an automation system of type AS 416 or higher.
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Siemens ST PCS 7 · November 2007
© Siemens AG 2007
• Setting of control parameters dependent on working point
The GainSched block has been designed for variable setting of
controller parameters depending on the working point in non-linear
controlled systems. The block functions similar to the polygon
block, and can derive three separate output variables from
the response of an input variable, and apply these as control parameters
for a linked controller block. The GainSched block then
adjusts the control parameters of the combined controller depending
on the response of the actual value.
The faceplate of the GainSched block can be called from the
faceplate of the associated controller.
• Monitoring of control quality
The ConPerMon block can be used to monitor the quality of a
controller block according to a patented procedure. The setpoint,
actual value and manipulated variable of the controller
block (e.g. PID controller) are connected to the ConPerMon
block which determines the control quality using these online
values. The block can trigger a warning or alarm depending on
the deviation from a reference value, e.g. the control quality determined
during commissioning.
The faceplate of the ConPerMon block can be called from the
faceplate of the associated controller. OS displays can be generated
during engineering which list all deviations in the control
quality of a plant or unit. The plant operator can use these displays
to recognize problems early, and to analyze and specifically
eliminate such before they result in serious deficiencies or
a production failure.
PID Tuner
The PID Tuner is a function integrated in the CFC for optimization
of the CTRL_PID and CTRL_S software controllers. The optimum
parameters for a control loop can then be determined for PID, PI
and P control modes in defined steps.
The tool is suitable for optimizing controlled systems with or without
an integral component. Optimization can be carried out in
manual or automatic mode. The transient response of the controllers
with the determined parameters can be checked by defining
jumps. The controller parameters can be saved, and recalled
as required.
During determination of the controller parameters, the typical
controller values (actual value, setpoint, manipulated variable)
are recorded by a trend function.