embedded fpga based self tuning controller for conical tank
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EMBEDDED FPGA BASED SELF TUNING CONTROLER FOR CONICAL TANK PROCESS
Students : S.Vignesh
M. Saravana Pandian
Dept : Instrumentation & Control Engg
From : Sethu Institute Of Technology
E.Mail : Vicky.guy665@gmail.com
Ph No : 7708808625
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INTRODUCTION
The conical tank process is designed to maintain the level of the tank for the
desired value .To ensure the desired value in the tank PI controller law is normally used.
In current practice the PI tuning process is performed manually by an engineering
technician. However, for better and more consistent quality, it is desired to use automated
PI tuning. The dynamics of the conical tank is dominated by the peristaltic pump. To
protect the pump, the control signal is restricted to lie in the interval [0,5] volts .The
pump also has significant friction, The sensor exhibit significant noise in addition ,the
tank area will change due to the height change. Hence, the conical tank process exhibits
nonlinear behavior in the parameters. Selftuning control is widely regarded as a method
that can potentially become a major industrial control technique.
The conical tank process is one of the highly non linear processes. So the
difficulty that arises in the identification of this system can be broadly classified into
three categories-complexities, non linearity and uncertainty. A selftuning controller is
ideally suited to deal with the three classes of difficulties.
Embedded based selftuning controller is designed to maintain the level of the tank
with the change in area with respect to the change in height. To ensure the level of the
conical tank process, a PI control law is designed and implemented in a normal way for a
small bandwidth . The feedback control is to maintain the output at the set point while
there have been unknown load disturbance and dynamic uncertainty, but if the constant
gain controller loses its performance in conical tank because, if the set point largely
deviated from the operating point leads to large overshoot in the process output, there is a
need for self tuning controller.
SELF TUNING CONTROLLERS
Self tuning controller is one that automatically tunes its parameters to obtain the
desired parameters of the closed loop system. Self tuning regulators combine a linear
controller with a parameter identification approach to provide a structure in which gains
of the controller are calculated on line. Self tuning controllers include estimation circuit,
controller design circuit and controller circuit.
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Block diagram of self tuning controller
1.1 MATHEMATICAL MODEL FOR CONICAL TANK
The conical tank level process considered for simulation study is the level, the inflow rate and the outflow rate of the tank are considered as the controlled variable ( h ), manipulated variable ( Qin ) and disturbance variable ( Qout )
respectively. The inlet flow Qin , is the control input to the system and the output is the
water level. It is assumed that Qin
the flow takes immediately..
is controlled directly and that a commanded change of
Where R - Maximum radius in m.H - Maximum height in m.h – Height at any time‘t’.r – Radius at any time‘t’.
CONTROLLER THEORY
The process is controlled by a controller that has adjustable parameters. It is to
determine a controller that satisfies some design criteria if the process and its
environment are known. This is called underlying design problem. The adaptive control
problem is then to find a method of adjusting the controller when the characteristics of
the process and its environment are unknown or changing. In direct adaptive control the
controller parameters are changed directly without the characteristics of the process and
its disturbances.
PI CONTROLLER
The transfer function for the first order process is given by
G(s) = K p
(τ s +
1)
The difference equation for the above process is
y(k ) = a * y(k −1) + b * u(k
−1)
a = exp( −samp _ time
)τ
b = K p * (1 − a)
From the above equation we can find the value of system parameters by using the
RLS algorithm, now the system gain isKp = b
1 − a
HARDWARE IMPLEMENTATION
INTRODUCTION
National Instruments Compact Reconfigurable I/O (RIO) is a small rugged
industrial control and acquisition system powered by Reconfigurable I/O (RIO) FPGA
technology for ultrahigh performance and customization. NI Compact RIO incorporates a
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real-time processor and reconfigurable FPGA for reliable stand-alone embedded or distributed
applications, and hot-swappable industrial I/O modules with built-in signal conditioning for direct
connection to sensors and actuators. Compact RIO represents a low-cost architecture with open access
to low-level hardware resources.
REAL-TIME PROCESSOR
The Compact RIO embedded system features an industrial 200 MHz Pentium class
processor . which reliably and deterministically executes your Lab VIEW Real-Time applications.
Choose from thousands of built-in Lab VIEW functions to build your multithreaded embedded system
for real-time control, analysis, data logging, and communication.
FIELD-PROGRAMMABLE GATE ARRAYS (FPGAs)
The Field-programmable gate arrays (FPGAs)FPGA devices are widely used by control and
acquisition system vendors because of their performance, reconfigurability, small size, and low
engineering development costs. FPGA based devices have been traditionally vendor defined rather
than user defined because of the complexity of the electronic design tools. Now you can take
advantage of user- programmable FPGAs to create highly optimized reconfigurable control and
acquisition systems with no knowledge of specialized hardware design languages such as VHDL. With
Compact RIO, you can design your own custom control or acquisition circuitry in
silicon with 25 ns timing/triggering resolution.
Field Programmable Gate Arrays
PERFORMANCE
Using Lab VIEW FPGA software and reconfigurable hardware technology, you can create
ultrahigh performance control and acquisition systems with Compact RIO. The FPGA circuitry is a
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parallel processing reconfigurable computing engine that executes your Lab VIEW application in
silicon circuitry on a chip. You can design your own custom control or acquisition circuitry in silicon
with 25 nanosecond timing/triggering resolution.
REAL-TIME CONTROL APPLICATION DESIGN
• RIO FPGA core application for input, output, communication, and control
• Time-critical loop for floating-point control, signal processing, analysis, and point by- point decision
making
• Normal-priority loop for embedded data logging, remote panel Web interface, and
Ethernet/serial communication
LABVIEW REAL-TIME DEVELOPMENT ENVIRONMENT
• Target configuration options including startup application execution settings and development,
Web, remote panel, and file server access
• Open FPGA VI reference function for programmatic bit stream download,
Communication interface reference and application start
• Deterministic real-time while loop thread synchronization with FPGA-generated interrupt
(IRQ)
• FPGA front panel control/indicator read/write for data transfer
• Data scaling/mapping functions for integer to floating-point engineering units’
conversion
• Real-Time FIFO data buffering
HARDWARE IMPLEMENTATION
The physical setup for conical tank process interfaced with PC loaded with RLS algorithm
through Lab VIEW and Compact Reconfigurable Input Output . The inflow of conical tank is controlled
by peristaltic pump and outflow is through hand valve.
The set point is given in terms of volts. The level in the tank is sensed by differential
pressure transmitter. The output of DPT is current, converted to voltage by
suitable signal conditioning circuit. (Connecting a 250Ω resistor across it)
The level 0mm corresponds to 1v and the level 600mm corresponds to 5v. The voltage output
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1-5v is then conditioned to 0-4v and it is fed to Compact RIO. The converted digital data is sent to
the PC.
The controller output is then fed to DAC. The converted analog value of range (1-5v) is then
converted into 4-20mA using V-I converter. The current output from V to I converter (4-20mA) vary
the frequency of peristaltic pump such that it regulate the flow in order to attain the desired level.
Front Panel
Block Diagram
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CONTROLLER OUTPUT FOR STEPPING INPUT
Response for Controller output
RESPONSE WITH STEPPING INPUT
Response for parameters
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CONTROLLER GAIN FOR STEPPING INPUT
CONCLUSION
The industrial conical tank has high nonlinearity due to the area get changed with change in
height. A self tuning regulator was designed for the conical tank which bounded the tank level
from saturation while maintaining the correct level.
This project detailed the indirect self tuning regulator design algorithm, which is a combination
of the on-line recursive least-squares and controller, the algorithm was implemented for the conical
tank. The initial values of the estimated plant parameter
vector θ and the covariance matrix P affect the transient performance of the closed loop
system and may possibly lead to tank level saturation. Hence they must be chosen carefully.
REFERENCES
1. Yanan Zhao, Emmanuel G.Collins, Jr., and David A.Cartes, Indirect self tuning regulator design
for an industrial weigh belt feeder, American Control Conference Anchorage, AK May 8-10,
2002.
2. M.Shangalov, H.M.Budman,’online adaptive parameter estimator design and tuning’, AACC,
2002.
3. Yasutoshi Mori, Masayoshi Doi and Yasuchika Mori,’A self tuning controller for systems with
varying time delays’, ICE, 2002.
4. K.M.Vu, G.A.Dumont and P.Tessier,’Recursive least determinant self tuning regulator’,
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IEEE, 2000.
5. Jinsiang Shaw, ‘chive vibration isolation by adaptive control’, IEEE, 1999.
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