Embedded Mechatronics System Design for Uncertain Environments: Linux®-based, Rasbpian®, ARDUINO® and MATLAB® xPC Target Approaches

Cover
Contents
Foreword
Acknowledgments
Outlines
1 Introduction
	1.1 Introduction to embedded system
	1.2 Example of embedded system using Athena III PC104
	1.3 Example of embedded systems using ARDUINO®
	1.4 Example of embedded system using Raspberry Pi
	1.5 Example of embedded system using PIC
	1.6 Motivations
	1.7 Systematic design approach for prototyping embedded systems
	References
2 Linux®-based embedded system design
	2.1 Linux® operating system
	2.2 Building Linux® for embedded systems
	2.3 Program layouts in Linux®
	2.4 System design and architecture
		2.4.1 Main process design
		2.4.2 Sensor process design
		2.4.3 Sensor fusion thread design
		2.4.4 Control process design
		2.4.5 Actuator driver design
		2.4.6 Network communication thread design
	2.5 Testing of components for control systems
		2.5.1 Inertial measurement unit
		2.5.2 DVL sensor unit
		2.5.3 Image video unit
		2.5.4 Depth sensor unit
	2.6 Kalman filter
	2.7 Graphical user interface
	References
3 Modeling and simulation of embedded underwater vehicle system
	3.1 Introduction
	3.2 Overview of remotely operated underwater vehicle
	3.3 Dynamics modeling of remotely operated underwater vehicle
		3.3.1 Hydrodynamic damping model
		3.3.2 Hydrodynamic-added mass model
	3.4 Validation of experimental results
		3.4.1 Heave model identification
		3.4.2 Yaw model identification
	3.5 Simulation of remotely operated underwater vehicle model
	3.6 Simulating external disturbance for remotely operated underwater vehicle model
	3.7 Launch and recovery process model
	3.8 Control systems design
		3.8.1 Sliding-mode control
		3.8.2 Proposed fuzzy-based genetic algorithm for SMC
		3.8.3 Proportional-integral-derivative
			3.8.3.1 Conventional SMC
	3.9 Remotely operated underwater vehicle sea trial
	References
4 xPC-Target embedded system design
	4.1 Introduction
	4.2 Overview of hardware interfacings for simulations testing
	4.3 Hardware interfacings
	4.4 Hardware-in-the-loop testing using xPC-Target
		4.4.1 Create xPC-Target real-time kernel using desktop PC as target PC
		4.4.2 Create xPC-Target real-time kernel using Athena II-PC104 as target PC
	4.5 Creating xPC-Target Simulink® block diagrams
	4.6 Using RS232, analog, and digital I/O in xPC-Target
	4.7 Infrared sensor model
	4.8 Incremental encoder model
	4.9 Identification of a servo DC motor
	4.10 PID speed control of servo DC motor
	4.11 Sliding-model speed control of servo DC motor
	4.12 Linear quadratic regulator
	4.13 Digital speed control of servo DC motor
	4.14 Case study: marine robotic vehicle with uncertainties using xPC-Target system
		4.14.1 System design and architecture
		4.14.2 Underwater robotic vehicle dynamic model
		4.14.3 Steady-state thruster's dynamics
		4.14.4 Underwater robotic vehicle—horizontal subsystem model
		4.14.5 Controller design
		4.14.6 Implementation and testing
	References
5 PIC embedded system design
	5.1 Overview of MPLAB IDE
	5.2 Intelligent vacuum robot system design
		5.2.1 System design and architecture
		5.2.2 Programming and system implementation
		5.2.3 Testing
	5.3 Remote temperature-sensing system design for patients
		5.3.1 System design and architecture
		5.3.2 Programming and system implementation
		5.3.3 Testing
	5.4 Wall-climbing robot system design
		5.4.1 System design and architecture
		5.4.2 Programming and system implementation
		5.4.3 Testing
	5.5 Magnetic conveyor system design
		5.5.1 System design and architecture
		5.5.2 Programming and system implementation
		5.5.3 Testing
	References
6 ARDUINO® embedded system design
	6.1 Remotely operated vehicle system design
		6.1.1 System design and architecture
		6.1.2 Programming and system implementation
		6.1.3 Testing
	6.2 Smart control of marine-tracked vehicle for surveillance
		6.2.1 System design and architecture
		6.2.2 Programming and system implementation
		6.2.3 Testing
	6.3 A sloth bear-inspired pole-climbing robot
		6.3.1 System design and architecture
		6.3.2 Programming and system implementation
		6.3.3 Testing
	References
7 Raspberry Pi-embedded system design
	7.1 Fouling detection system
		7.1.1 System design and architecture
			7.1.1.1 First-boot procedures
			7.1.1.2 Installing Raspberry Pi cam
			7.1.1.3 Setting up Wi-Fi to enable remote control for Raspberry Pi
			7.1.1.4 Remotely copy files to and from Raspberry Pi
			7.1.1.5 Remotely controlling Raspberry Pi terminal
			7.1.1.6 Set up database and PHP webpage
			7.1.1.7 Installing MySQL and Easyphp and PhpMyAdmin on computer
			7.1.1.8 Installing MySQL on Raspberry Pi
			7.1.1.9 Creation of database
			7.1.1.10 PHP template for uploading images to the database
			7.1.1.11 OpenCV
		7.1.2 Programming and system implementation
			7.1.2.1 Haar cascade object recognition
			7.1.2.2 Merging the vector files and training the cascade
			7.1.2.3 Artificial neural networks identification
		7.1.3 Testing
	7.2 Multi-hop microprocessor-based prototype system for remote vibration and image monitoring
		7.2.1 System design and architecture
		7.2.2 Programming and system implementation
		7.2.3 Testing
	7.3 Face recognition system
		7.3.1 System design and architecture
		7.3.2 Programming and system implementation
		7.3.3 GUI using PyQt
		7.3.4 Testing
	References
Index
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