development of a matlab data acquisition and control toolbox for pic microcontrollers

Development of a Matlab Data Acquisition and Control Toolbox for PIC Microcontrollers

Mechanical Engineering SeminarMarch 27, 2007

Sang-Hoon LeeDepartment of Mechanical, Aerospace, and Manufacturing Engineering

Polytechnic University, Brooklyn, NY 11201

Matlab Data Acquisition and Control Toolbox for PICs 2007

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• Background

• Motivation

• Goals

• Prior Research

• Hardware Environment

• Software Environment

• Integration of Simulink and PIC

• Programming the PIC microcontroller

• Illustrative Example

• Conclusion

Outline


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Background: Data Acquisition• Data acquisition (DAQ) refers to automatic acquisition of real-world sensory

information

• DAQ is used for test instruments, condition monitoring of industrial machinery, process industry, medical instruments, environment monitoring, robotics, etc.

• DAQ can be used to develop virtual instruments for productivity enhancement


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Background: Data Acquisition and Control• DAQ systems are useful for monitoring and data analysis but if one needs to command a real-

world device into action based on the measurement of some real-world phenomenon, then a DAQ system is not sufficient

In this case one needs a data acquisition and control (DAC) system

• A DAC system

collects data from sensors, and

using computing resources of a PC or an on-board computer processes sensory information, computes control command, and commands control actuators


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• Peripheral Interface Controllers (PICs)

– Inexpensive microcontroller units (few dollars) that include

• Central processing unit

• Peripherals: memory, timers, and I/O functions

– Provide functionality for multitude of applications (e.g., automobile, consumer

electronics, safety/security, telecommunication)

– Popular in educational, hobby, and industrial applications

Background: PIC


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• PC-based data acquisition and control (DAC) boards– High-end DAC boards (e.g., Quanser’s MultiQ3, National Instruments, etc.)

– Advanced hardware capabilities and sophisticated software environment

– Drawback: cost! (high hundreds to few thousand dollars)

Motivation—I

8 Analog Inputs

8 Analog Outputs

8 Encoder Signals

Digital I/Os

Terminal Board

MultiQ3 ISA DAC Board


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• Data Acquisition and Control (DAC) Boards– Low-end DAC boards

– Relatively low cost

– Drawback: use proprietary software

– DAC boards supported by Matlab

– Costly and usually include additional hardware features that may not be fully used (e.g., high sampling rates and high resolution analog to digital converter)

Motivation—II


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• Create a Matlab DAC toolbox for PIC microcontrollers

– Exploit serial communication capability of PIC microcontrollers and Matlab software

– Use icon-based programming environment of Simulink

– Illustrate the integration of low-cost PIC microcontrollers with Matlab DAC toolbox environment

• Use the Matlab DAC toolbox to facilitate– Automatic generation of proper PIC assembly codes for a variety of sensors and actuators

– Automatic programming of the PIC microcontroller

– Data communication between the PIC microcontroller and Matlab

Goals


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• Basic Stamp 2 (BS2) microcontroller to LabVIEW interface by Radcliffe, 2001

• GUI capabilities for PIC microcontroller via a Matlab interface by Lee et al., 2004

• Matlab data acquisition and control toolbox for BS2 microcontroller by Panda et al., 2004

Prior Research

LabVIEW interface with BS2 Matlab DAC for BS2


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Hardware Environment

PC and PIC development board

• PIC development board consisting of– PIC16F74 microcontroller with a 20MHz crystal oscillator– MAX232 with five 1μF capacitors– DB-9 connector

• PIC development board transmits/receives data to/from a PC via MAX232• PIC-PG2C programmer

– Receives power from the PC’s serial port – IC-Prog to download PIC HEX code to the PIC microcontroller

PIC-PG2C programmer and PIC


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• Matlab – An interactive technical computing software

• Simulink – Matlab’s icon-based programming environment

• The PIC assembly language– A primitive programming language (35 single-word instruction set)

• A newly developed Simulink library for the PIC microcontroller– Automatically produces and downloads the proper PIC assembly code to the m

icrocontroller– Allows data communication between the PIC microcontroller and Matlab

• MPASM• IC-Prog

Software Environment I


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• Sample PIC assembly code to Blink an LED

; LED blink

__CONFIG _CP_OFF & _WDT_OFF & _HS_OSC & _PWRTE_ON

list P=16F74 include "p16f74.inc"

temp EQU 20h temp1 EQU 21h temp2 EQU 22h

ORG 0x00GOTO START

START BSF STATUS,5MOVLW 0x00MOVWF TRISBCLRF PORTB

BEGINBCF PORTB,0;CALL DELAY

Aside: PIC Assembly Programming GOTO BEGINDELAY

MOVLW 0x3f

MOVWF tempw MOVLW 0xff MOVWF temp2w1 MOVLW 0xff

MOVWF temp1w2 DECFSZ temp1

GOTO w2DECFSZ temp2

GOTO w1DECFSZ temp

GOTO wRETURN

END


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• Template.mdl model file– Predesigned Simulink model file for interaction with the PIC microcontroller– Must be used to design Simulink block diagrams for interaction with the PIC mic

rocontroller– TotalCompile has been embedded within the callback parameters

Software EnvironmentII

Template and model properties


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• PIC Library

– Custom library of Simulink blocks for interaction with sensors and actuators connected t

o the PIC microcontroller

– Construct a Simulink block diagram by dragging and dropping blocks into the Template

model file

– IOBlock

– Digital input/output

– PinStateIn block (8 channels)

– PinStateOut block (8 channels)

– Analog input/output

– ADC block (8 channels)

– PWM block (2 channels)

Software Environment III

PIC Library


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• ADC block

– Use the 8-bit analog to digital conversion module of the PIC microcontroller

Software Environment IV

ADC block and parameter


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• PWM block

– Use the PWM modules of the PIC microcontroller

– Produce the required analog voltage output by varying the duty cycle of the PWM

signal

Software Environment V

PWM block and parameter


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• IOBlock

– Initiate serial communication between Matlab and the PIC

– Transmit/receive data between Matlab and the PIC

– Terminate serial communication between Matlab and the PIC

– Compute the average sampling period for Simulink block diagram execution

Software Environment VI

IOBlock and parameters


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• Template file is used to construct a Simulink block diagram

• Before the start of the Simulink block diagram a Matlab function (TotalCompile) is ex

ecuted in the following sequence

– Declare global variables

– Categorize and specify sensor and actuator blocks used in the Simulink diagram

– Generate a PIC assembly code

– For each sensor/actuator block in the PIC Library the corresponding PIC assembly code

has already been created and saved as an m-file

– Generate a portion of the IOBlock Matlab code

– Program the PIC microcontroller

• At the start of the Simulink block diagram the IOBlock is executed first

Integration of Simulink and PIC


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• PIC assembly code is generated by TotalCompile

• PIC assembly code is converted to PIC HEX code by the MPASM assembler

• PIC HEX code is downloaded by IC-Prog via the serial port

Flow diagram of programming the PIC microcontroller

Programming the PIC microcontroller I


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Aside: LED Blinker Simulink Diagram


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LIST p=16f

74

INCLUDE "p16f74.inc"

__CONFIG _CP_OFF & _WD

T_OFF & _HS_OSC & _PWR

TE_ON

temp EQU

20h

temp1 EQU

21h

tempval EQU

22h

ORG 0

CLRF STATUS

GOTO BootStart

BootStart

BANKSEL PORTA

CLRF PORTA

CLRF PORTB

CLRF PORTC

CLRF PORTD

BANKSEL TRISA

MOVLW b'1111111

1'

Aside: LED Blinker Code from Matlab ToolboxMOVWF TRISA

MOVLW b'1111111

1'

MOVWF TRISB

MOVLW b'0000000

0'

MOVWF TRISD

ADCInitialization

BCF STATUS,

RP0

MOVLW B'1000000

1'

MOVWF ADCON0

BSF STATUS,R

P0

MOVLW b'0000000

0'

MOVWF ADCON1

USARTinitialization

BSF STATUS,

RP0

MOVLW b'00000001'

MOVWF OPTION_REG

BCF STATUS, RP0

MOVLW b'1000010

0'

MOVWF INTCON

CLRF TMR0

BaudRateSettingsforUSART

BSF STATUS,

RP0

MOVLW d'10'

MOVWF SPBRG

MOVLW b'0010010

0'

MOVWF TXSTA

BANKSEL RCSTA

MOVLW b'1001000

0'

MOVWF RCSTA

MOVF RCREG, W

MOVF RCREG, W

MOVF RCREG, W

PWMinitialization

BSF T2CON, T2CKPS1

BSF T2CON, TMR2ON

BSF STATUS, RP0

MOVLW d'250'

MOVWF PR2

BCF TRISC, 1

BCF TRISC, 2

BCF STATUS, RP0

CLRF CCP1CON

BSF CCP1CON, CCP1M3

BSF CCP1CON, CCP1M2

CLRF CCP2CON

BSF CCP2CON, CCP2M3

BSF CCP2CON, CCP2M2

Main

receive1

BCF STATUS,

RP0

BCF STATUS,

RP1

BTFSS PIR1,RCIF

GOTO receive1

MOVF RCREG,W

MOVWF tempval

compare1

BTFSS tempval,0

GOTO skp1

BSF PORTD, 1

GOTO jmp1

skp1

BCF PORTD, 1

jmp1

NOP

GOTO Main

END


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• Position control of a DC motor is performed to show the efficacy of Matlab data

acquisition and control toolbox

• The testbed has a DC motor, a continuous rotation potentiometer, and a power module

Hardware layer schematic

Illustrative Example–I


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• A PID controller is used for position control of the DC motor

– ADC_Pot block for the analog output of the potentiometer

– PWM_Motor block for the analog input to the motor

Simulink block diagram

Illustrative Example–II


24DC motor angular position tracking response

• Experimental setup for the DC motor angular position

– PID controller (KP=1.43, KI=1.97, and KD=0.5)

– Simulink’s ODE4 (Runge-Kutta) algorithm with a sampling period of 0.13 second

• Experimental response of the DC motor angular position

– An average 2% settling time of 5.9 seconds and a percentage overshoot of 18.25%

Illustrative Example–III


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• Developed a low-cost Matlab Data Acquisition and Control Toolbox for PIC microcontrollers by exploiting

– Matlab and Simulink

– Serial communication capabilities of Matlab and PIC

• Data Acquisition and Control Toolbox designed using our framework allows the user to focus on

– Hardware-in-the-loop implementation

– Experimental validation

– Industry-style rapid control prototyping

• Our framework allows the use of a microcontroller as a low-cost data acquisition and control board

Conclusion

development of a matlab data acquisition and control toolbox for pic microcontrollers

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