Sticky Notes

This blog is officially closed. Do check out the new blog at

Wednesday, June 29, 2011

A Tough Competition

This year, it is going to be a tough game. Or Loy Krathong game. Whichever applies. Last year, barely any teams can achieve Robo-Pharaoh but this year, most teams can achieve Loy Krathong.

Is the standard of International ROBOCON is getting higher? Or the game is relatively easy compared to last year.

This is Hong Kong ROBOCON Final Video. Quite fast.

This is Mongolia ROBOCON Video. Quite fast too and with Loy Krathong winning.

And we have yet to see from the grandchampion of ABU ROBOCON, China...

Friday, June 24, 2011

Phototransistor Line Finder with Fuzzy Logic Part I

The secret to a good line following is to have a good sensor. In UTM ROBOCON, we have tried many kinds of sensors.

The first type is IR transmitters and receivers with operational amplifier as comparator. This is the most basic and simple type of line sensors. But this is also the most vulnerable to noise and light intensity changes. It is good to use this under florescent lighting but in spot light, not too good. And this sensor cannot cope with different floor colours. This page provides example of a comparator circuit.

The second type is industrial grade sensors. A good example is the FX301 digital fibre sensors. This type of sensors could easily be obtained from Cytron. This sensor is very common in the recent Malaysia ROBOCON 2011 game. Few teams uses RGB sensors that can detect multiple colour. I think it is a product from Keyence. This sensor is more robust than a IR sensors. The limitation of this sensor and the IR transmitter is that they only provide digital data. In other words, the line position was given in binary.

The third type is a phototransistor / photocell / photodiode sensors. This sensor is very similar to the IR type but the data was fed directly into microcontrollers. Well, this is a bit of history regarding this sensor. It was initially developed in UTM ROBOCON 2009 where the old version uses photocell. Of course there are some limitation in photocell compared to phototransistors or photodiode. Development was halted in UTM ROBOCON 2010 but in 2011, it was revived back. Now with phototransistors version.

With the data directly fed into the microcontroller, line position can be obtained using self designed algorithm. We have tried fuzzy logic and it worked just fine. The advantage of this sensor is they can provide a continuous line position value compared to the first two type. But this sensors is not without disadvantage. They are hyper-ly sensitive to spot light.

Thursday, June 23, 2011

News - UTM won first and second place in the National Robocon 2011 Competition

UTM Robocon Team has once again proved their mettle in the National Robocon 2011 Competition when they secured first and second place in the competition held in the USIM on 13 to 18 June 2011.

ROBOCON is a robot design competition organised by the Ministry of Higher Education (MOHE), Radio Television Malaysia (RTM) and SIRIM Berhad which aims to provide opportunities for university students to develop their potential and creativity in the field of robotics.

The National Robocon 2011 Competition is themed “Hibiscus: Unity for 1 Nation”, in which each team had to create a hibiscus which is our national flower. The team which could build a complete hibiscus in three minutes was given a “Mekar” (Blossom). UTM 2011 Robocon team
consisted of 25 students from the Faculty of Electrical Engineering and Faculty of Mechanical Engineering.

UTM sent three teams to the Robocon 2011 Competition and all the teams qualified for the quarter-final round after winning in their respective groups and the game in the second round. In the semifinals, the UTM B team defeated teams from Multimedia University (MMU) and UTM C team defeated a team from the University of Petronas (UTP).

What is most encouraging is that both winnings achieved the “Mekar”. UTM B team managed to become champion by beating UTM C team at the end by doing “Mekar”.

During the Robocon 2011 Competition, only three teams from UTM were able to do “Mekar” with UTM B doing it six times out of eight games.

As a result, UTM B won a cash prize of RM10, 000, and UTM C winning RM 7,000 as runner-up. UTM B was also selected as the Best Engineering Award winning prizes worth RM 3,000.

The UTM 2011 Robocon team has once again been chosen to represent Malaysia at the International Robocon Competition in Bangkok, Thailand in August 2011.


Grabbed from NewsHub at UTM

Sunday, June 19, 2011

Congratulations to UTM

Champion: UTM B
First Runner up: UTM C
Best Engineering Award: UTM B

Thursday, June 9, 2011

Fuzzy Logic Controller for Motor Speed Control

Basic Setup
Motor speed control is the most important thing in navigation aside good feedback sensors. Here, the fuzzy logic controller is discussed to control the speed of motor.

Basic setup for this controller is a Vexta Brushless motor and a rotary encoder with 500 pulse per revolution. The controller output is actually the pulse width modulation duty cycle for the brushless motor.

The block diagram for the whole system is a position controller, fed into a fuzzy logic controller as speed control and then fed into an integrator before feeding into the vexta motor PWM.

Fuzzy Logic Controller 
To design this fuzzy logic controller, two inputs are needed; the error of speed and the derivative of error of speed. Then rules is developed to decide on the amount of "acceleration" to be fed into the integrator.

A 5 X 5 matrix rule is used to decide on amount of integration. These are few examples:

* IF desired speed to much more than actual speed, AND IF acceleration is zero, THEN integrate more positive value.
* IF desired speed is much less than actual speed, AND IF acceleration is negative, THEN integrate with less negative value.
* IF desired speed is equal to actual speed, AND IF acceleration is zero, THEN integrate with zero value.

A complete list of rules is setup and the typical fuzzy logic controller is designed. Some basic block are the fuzzifier, implication, inferencing, and defuzzifier.

The fuzzy logic controller was successfully implemented to control the speed of a vexta motor. The motion profile is depicted in the diagram below.

Figure 1: Data logged using PIC and MATLAB via RS232 connection.

* The controller will give the desired speed but the acceleration and deceleration profile is not really smooth. Better controller is needed to have a straight ramped acceleration and deceleration profile.
* This controller will give minor pole near the imaginary axis (seen from the oscillation at speed steady state value). This might also caused by quantization error from the encoder. Better filter is required to filter out this noise.
Related Posts Plugin for WordPress, Blogger...