Control System Algorithm | Engineering Dissertations

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Executive Summary


Traditionally development of microprocessor based control systems involved the following steps. The control algorithm was designed by a systems or a control engineer. The algorithm would then be coded in programming languages like assembly, C or C++ which would be implemented on a microprocessor based hardware – the controller.

The problem with this method was the verification of the algorithm would be possible only once the whole system was developed. Any errors in design would prove extremely costly. Also in converting control logic specification into software there is a high probability of translation errors that would lead to erroneous results.

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mModel Based Design is a software methodology which addresses these issues and is gaining a lot of popularity currently in the industry.

The scope of this project is to apply the Model Based Design methodology to develop a control algorithm that eases the parallel parking of a car problem for a novice driver.

Aims and Objectives

The aim of this project is to develop a parallel parking system using Model Based Design. The objectives are to understand the parallel parking problem and methods to solve it, steps involved in Model Based Design and explore the possibility of implementation of a parallel parking algorithm on a Lego Mindstorms Robotics Kit.


A fuzzy logic based parallel parking algorithm was successfully simulated. Model Based Design concepts were explored and implemented in the design. Programs developed in Simulink were successfully tested on the Lego Mindstorms KIT using Real Time Workshop Embedded Coder, EC Robot Toolbox, nxtOSEK and other associated tools.


The parallel parking strategy implemented did show good results. However, real life scenarios may be different than the one discussed. For example, the controller depends on wall following. This implies there has to be 3 sides closed in a gap for the parking controller to work.

The development of the algorithm was with the intent of being able to execute it on a Lego Mindstorms Kit. However, there were some issues regarding this. The main being lack of a floating point unit on the NXT Brick. Though it is possible to execute floating point programs on the NXT, it causes severe performance issues.

The controller developed used the fuzzy logic blockset which inherently uses a lot of floating point variables. One method to overcome this draw back could be developing a fixed point version of the fuzzy logic blockset.

Other parking strategies involving classical control could be experimented with Lego Mindstorms. Complex tasks like path planning could be executed on a computer communicating with the NXT via Bluetooth and the control tasks could be implemented on the NXT using fixed point math.

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