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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.