swpid, Instrukcje, National INSTRUMENTS, Pdf
[ Pobierz całość w formacie PDF ]
LabVIEW
PID Control Algorithms
PID Control Toolset
PID Tools
P, PI, PD, and PID
Error-squared PID
Lead-lag compensation
Setpoint ramp generation
Autotuning
Gain scheduling
Two degree of freedom PID control
Multiloop cascade control
Feedforward control
Override (min/max selector) control
Ratio/bias control
Integrator antiwindup
Bumpless automatic-to-manual and
manual-to-automatic transfer
Fuzzy Logic Tools
Graphical user interface for easy
development of fuzzy logic
controllers
VIs for implementation of fuzzy
control
Up to four controller inputs and
one output per fuzzy controller
Cascade multiple controllers for
complex control
Overview
The PID Control Toolset add sophisticated control algorithms to
your instrumentation software development system. By
combining the PID and fuzzy logic control functions in this
toolset with the math and logic functions in LabVIEW, you can
quickly develop programs for automated control.
with respect to parameters such as risetime and overshoot. This
method maintains closed-loop control during the tuning process,
therefore maintaining stability of the system controlled. The PID
Tools also feature gain scheduling. You can improve performance
in defining several regions of operation for the controller.
PID Control Examples
Examples for process control included in the PID Control Toolset
are:
• Simulation VIs
• Tank Level
• General PID
• Plant Simulator
• Cascade and Selector
• PID with MIO Board
• Lead-Lag
PID Tools
The PID functions implement a wide range of PID algorithms
with error-squared and external-reset feedback. They also
implement lead-lag compensation and setpoint ramp
generation. Control strategies include multiloop cascade,
feedforward, minimum and maximum override, and ratio/bias.
The PID algorithms feature bumpless auto/manual transfer,
antireset windup, direct/inverse action, manual output
adjustment, and a run/hold switch.
Fuzzy Logic Tools
Fuzzy logic can be used to accelerate development of control for
nonlinear or highly complex systems. It is easy to comprehend
because the control strategy is implemented with simple,
intuitive, linguistic rules. Thus, the need for highly complex and
difficult-to-understand control strategies is eliminated. In addition
to control applications, the fuzzy logic software can be used for
expert decision making, such as pattern recognition or fault
diagnosis. In addition to helping you design your control system,
this point-and-click fuzzy logic software includes functions for
implementing your fuzzy control system in LabVIEW.
Control Strategy Design
You can design PID control strategies, scale I/O values from
engineering units to percentages, and set up timing of the PID
algorithms. Finally, you can use tuning procedures for both
Closed-Loop (Ultimate Gain) and Open-Loop (Step Test).
Autotuning
Autotuning can be used to automatically improve the
performance of your stable P, PI, or PID controller. The
autotuning algorithm is a setpoint relay feedback method that
automatically tests the control system to determine new PID
parameters that will improve the performance of the controller
National Instruments
Phone: (512) 794-0100 • Fax: (512) 683-8411 • info@natinst.com • www.natinst.com
93
LabVIEW
PID Control Algorithms
Fuzzy Logic Control Designer
Each fuzzy controller can have up to four inputs and one output.
For systems with large numbers of controller inputs, you can
cascade multiple fuzzy controllers for control while
implementing rules that are easy to understand. Linguistic terms
for rules are defined with membership functions of the following
shapes – triangular, trapezoidal, Z-shaped, S-shaped, or
singleton. Rules are generated automatically to create a
complete rule base of all possible combinations of inputs using
the interactive fuzzy logic software. The output of each rule is
manually selected and weight values may be assigned for the
purpose of controller tuning. Defuzzification methods include
Center of Area, Center of Maximum, and Mean of Maximum. All
designed controller information is stored in a data file for
implementation in the application.
control examples, a pattern recognition example, and an
example of implementing a fuzzy controller with DAQ functions.
Membership Functions
Triangular
Trapezoidal
Z-shaped
S-shaped
Singleton
Defuzzification Methods
Center of Area
Center of Maximum
Mean of Maximum
Controller VIs
This toolset includes VIs to be used in your application for control
or decision making. All controller information from the fuzzy
logic control designer is saved to a data file and is retrieved and
grouped into a single cluster with the Load Fuzzy Controller VI.
This cluster of information is wired in your application to the
Fuzzy Controller VI. Controller inputs are wired into this VI and
the controller output is calculated, based on your designed
controller, and returned to your application. You can easily
integrate fuzzy logic with NI-DAQ and data acquisition
hardware. Examples provided with the software include fuzzy
Ordering Information
PID Control Toolset for LabVIEW/BridgeVIEW
Windows NT/98/95/3.1..............................777874-03
Contact your local National Instruments office for
additional platform options.
94
National Instruments
Phone: (512) 794-0100 • Fax: (512) 683-8411 • info@natinst.com • www.natinst.com
[ Pobierz całość w formacie PDF ]