Feedback control with LEGO mindstorms

Abstract

Feedback control system is commonly used in any kind of applications. It allows the system to produce the desired output by using the feedback information. For instance, take an air conditioning system as an example. An air conditioning system is used to condition the temperature and humidity level in a closed environment. Each of the air conditioning system comes with a range of temperature which the system could control. Users would select their desired temperature and system will adjust the temperature to match the user selection. However, air conditioning system may be use in different environment and the temperature of the room may change from time to time. The system needs to know how much power is needed for the cooling component to maintain the temperature at the desired level. In this example, the feedback information would be the temperature. The system will measure the temperature every once in a while. If the temperature is too high, the system will increase the cooling power. And when the temperature falls too low, it will decrease the cooling power. The temperature in the room may not be exactly the same as what the user has selected, but with feedback control system, it can maintain the temperature as close as possible to the desired temperature. However, in the example mentioned earlier, the output of the system does not have to be exactly the same as the desired output. Since human are not sensitive to temperature changes within 1 Degree Celsius, the air conditioning system has a large tolerance. Where as in application which involve real time or quick response, the time taken for the feedback may very well affect the whole feedback control system. In this project, the scope will be on balancing application such as Segway. Segway is a two-wheeled, self-balancing, vehicle [1]. For such application, slow feedback response may cause the vehicle to lose its balance. A two-wheeled robot built using LEGO MINDSTORMS EV3 was used to model the Segway applications. Experiments were carried out to test how the performance decrease when the system receive slow feedbacks.