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Microcontroller Based Supervisory Control of a Solar Tracker

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Microcontroller Based Supervisory Control of a Solar Tracker

Searle, Kevin (2016) Microcontroller Based Supervisory Control of a Solar Tracker. Masters thesis, Concordia University.

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Abstract

The Supervisory Control theory (SCT) of Discrete-Event Systems is concerned with the design of supervisors that can generate appropriate control command sequences that meet the plant design specifications. Examples of these sequences include the startup and shut-down command sequences of a spacecraft engine.
This thesis addresses the implementation of Supervisory Controller (SC) executing on microcontroller hardware. The plant studied is a 2 degree-of-freedom solar tracker.
Existing implementations of Supervisory Control Theory focus on Programmable Logic Controller (PLC) based systems. PLCs are mainly used in process control and manufacturing applications. These implementations have proven advantages but suffer from numerous drawbacks. The hardware is large, expensive and over engineered for many embedded system applications. Additionally, a number of disconnects between Supervisory Control Theory and their practical application exist. These include but are not limited to: the Avalanche Effect, Inexact Synchronization and Simultaneous Events.
This thesis extends the application of SCT to the field of microcontroller-based embedded systems. Methods to minimize or remove the effects of Avalanche Effect, Inexact Synchronization, and Simultaneous Events are analyzed in a microcontroller-based environment.
Additionally, design procedures for the modelling and implementation of a supervisory controller executing within a microcontroller are explored. To this end, a physical implementation of a real system was created and documented. An offline computation of the system supervisor is derived in MATLAB and stored in the system’s onboard memory as a State Transition Table (STT). An optimized storage method is developed that allows for fast execution of state transitions and a low memory footprint.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Searle, Kevin
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:22 December 2016
Thesis Supervisor(s):Hashtrudi Zad:, Shahin
ID Code:982084
Deposited By: KEVIN SEARLE
Deposited On:09 Jun 2017 14:19
Last Modified:18 Jan 2018 17:54
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