Muutke küpsiste eelistusi

E-raamat: Embedded Mechatronics System Design for Uncertain Environments: Linux(R)-based, Rasbpian(R), ARDUINO(R) and MATLAB(R) xPC Target Approaches

(Newcastle University at Singapore, Singapore)
  • Formaat: EPUB+DRM
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 14-Dec-2018
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785613234
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 227,50 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
Embedded Mechatronics System Design for Uncertain Environments: Linux(R)-based, Rasbpian(R), ARDUINO(R) and MATLAB(R) xPC Target ApproachesSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 14-Dec-2018
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785613234
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

Industrial machines, automobiles, airplanes, robots, and machines are among the myriad possible hosts of embedded systems. The author researches robotic vehicles and remote operated vehicles (ROVs), especially Underwater Robotic Vehicles (URVs), used for a wide range of applications such as exploring oceans, monitoring environments, and supporting operations in extreme environments.

Embedded Mechatronics System Design for Uncertain Environments has been prepared for those who seek to easily develop and design embedded systems for control purposes in robotic vehicles. It reflects the multi-disciplinarily of embedded systems from initial concepts (mechanical and electrical) to the modelling and simulation (mathematical relationships), creating graphical-user interface (software) and their actual implementations (mechatronics system testing). The author proposes new solutions for the prototyping, simulation, testing, and design of real-time systems using standard PC hardware including Linux, Raspbian, Arduino, and MATLAB xPC Target.



Industrial machines, automobiles, airplanes, robots, and machines are among the myriad possible hosts of embedded systems. This book has been prepared for those who seek to easily develop and design embedded systems for control purposes in robotic vehicles.

Foreword xi
Acknowledgments xiii
Outlines xv
1 Introduction
1(16)
1.1 Introduction to embedded system
1(1)
1.2 Example of embedded system using Athena III PC 104
2(1)
1.3 Example of embedded systems using ARDUINO®
3(2)
1.4 Example of embedded system using Raspberry Pi
5(2)
1.5 Example of embedded system using PIC
7(1)
1.6 Motivations
8(2)
1.7 Systematic design approach for prototyping embedded systems
10(7)
References
15(2)
2 Linux®-based embedded system design
17(52)
2.1 Linux® operating system
17(3)
2.2 Building Linux® for embedded systems
20(5)
2.3 Program layouts in Linux®
25(2)
2.4 System design and architecture
27(15)
2.4.1 Main process design
30(3)
2.4.2 Sensor process design
33(4)
2.4.3 Sensor fusion thread design
37(2)
2.4.4 Control process design
39(1)
2.4.5 Actuator driver design
39(1)
2.4.6 Network communication thread design
40(2)
2.5 Testing of components for control systems
42(17)
2.5.1 Inertial measurement unit
42(5)
2.5.2 DVL sensor unit
47(3)
2.5.3 Image video unit
50(6)
2.5.4 Depth sensor unit
56(3)
2.6 Kalman filter
59(1)
2.7 Graphical user interface
59(10)
References
67(2)
3 Modeling and simulation of embedded underwater vehicle system
69(52)
3.1 Introduction
69(1)
3.2 Overview of remotely operated underwater vehicle
69(2)
3.3 Dynamics modeling of remotely operated underwater vehicle
71(13)
3.3.1 Hydrodynamic damping model
73(6)
3.3.2 Hydrodynamic-added mass model
79(5)
3.4 Validation of experimental results
84(8)
3.4.1 Heave model identification
84(4)
3.4.2 Yaw model identification
88(4)
3.5 Simulation of remotely operated underwater vehicle model
92(5)
3.6 Simulating external disturbance for remotely operated underwater vehicle model
97(4)
3.7 Launch and recovery process model
101(1)
3.8 Control systems design
102(15)
3.8.1 Sliding-mode control
104(1)
3.8.2 Proposed fuzzy-based genetic algorithm for SMC
105(5)
3.8.3 Proportional-integral-derivative
110(7)
3.9 Remotely operated underwater vehicle sea trial
117(4)
References
119(2)
4 xPC-Target embedded system design
121(90)
4.1 Introduction
121(2)
4.2 Overview of hardware interfacings for simulations testing
123(1)
4.3 Hardware interfacings
124(10)
4.4 Hardware-in-the-loop testing using xPC-Target
134(8)
4.4.1 Create xPC-Target real-time kernel using desktop PC as target PC
136(3)
4.4.2 Create xPC-Target real-time kernel using Athena II-PC104 as target PC
139(3)
4.5 Creating xPC-Target Simulink® block diagrams
142(9)
4.6 Using RS232, analog, and digital I/O in xPC-Target
151(7)
4.7 Infrared sensor model
158(1)
4.8 Incremental encoder model
159(5)
4.9 Identification of a servo DC motor
164(4)
4.10 PID speed control of servo DC motor
168(1)
4.11 Sliding-model speed control of servo DC motor
169(2)
4.12 Linear quadratic regulator
171(4)
4.13 Digital speed control of servo DC motor
175(2)
4.14 Case study: marine robotic vehicle with uncertainties using xPC-Target system
177(34)
4.14.1 System design and architecture
178(3)
4.14.2 Underwater robotic vehicle dynamic model
181(2)
4.14.3 Steady-state thruster's dynamics
183(5)
4.14.4 Underwater robotic vehicle---horizontal subsystem model
188(11)
4.14.5 Controller design
199(3)
4.14.6 Implementation and testing
202(5)
References
207(4)
5 PIC embedded system design
211(80)
5.1 Overview of MPLAB IDE
211(1)
5.2 Intelligent vacuum robot system design
212(23)
5.2.1 System design and architecture
212(4)
5.2.2 Programming and system implementation
216(18)
5.2.3 Testing
234(1)
5.3 Remote temperature-sensing system design for patients
235(8)
5.3.1 System design and architecture
236(4)
5.3.2 Programming and system implementation
240(1)
5.3.3 Testing
241(2)
5.4 Wall-climbing robot system design
243(17)
5.4.1 System design and architecture
245(8)
5.4.2 Programming and system implementation
253(6)
5.4.3 Testing
259(1)
5.5 Magnetic conveyor system design
260(31)
5.5.1 System design and architecture
261(13)
5.5.2 Programming and system implementation
274(10)
5.5.3 Testing
284(3)
References
287(4)
6 ARDUINO® embedded system design
291(54)
6.1 Remotely operated vehicle system design
291(22)
6.1.1 System design and architecture
291(12)
6.1.2 Programming and system implementation
303(4)
6.1.3 Testing
307(6)
6.2 Smart control of marine-tracked vehicle for surveillance
313(14)
6.2.1 System design and architecture
314(6)
6.2.2 Programming and system implementation
320(5)
6.2.3 Testing
325(2)
6.3 A sloth bear-inspired pole-climbing robot
327(18)
6.3.1 System design and architecture
327(8)
6.3.2 Programming and system implementation
335(8)
6.3.3 Testing
343(1)
References
344(1)
7 Raspberry Pi-embedded system design
345(96)
7.1 Fouling detection system
345(42)
7.1.1 System design and architecture
347(20)
7.1.2 Programming and system implementation
367(14)
7.1.3 Testing
381(6)
7.2 Multi-hop microprocessor-based prototype system for remote vibration and image monitoring
387(12)
7.2.1 System design and architecture
388(6)
7.2.2 Programming and system implementation
394(1)
7.2.3 Testing
395(4)
7.3 Face recognition system
399(42)
7.3.1 System design and architecture
399(1)
7.3.2 Programming and system implementation
399(20)
7.3.3 GUI using PyQt
419(2)
7.3.4 Testing
421(17)
References
438(3)
Index 441
Cheng Siong Chin is an Associate Professor at Newcastle University at Singapore where he has established research projects with partners from Seagate, Soil Machine Dynamics (SMD), SembCorp Marine, Visenti(Xylem), Temasek Polytechnic and Singapore Maritime Institute (SMI). He is also an Adjunct Professor to Chongqing University. He has also supervised projects on the intelligent systems design and simulation of complex systems in uncertain environment. He has published over 100 journal papers, books, book chapters, and conference papers. He currently holds 3 U.S. Patents, 2 provisional US patent applications, 1 Singapore Provisional Patent and 2 Trade Secrets in electronics and measurement systems. He obtained 2 research grants from SMI and 4 EDB-Industrial Postgraduate Programme (IPP) grants in the areas of intelligent systems design, simulation, and predictive analytics. He is a Fellow of the Higher-Education Academy, Fellow of IMarEST, Senior Member of IEEE and the IET, and a Chartered Engineer. He received the Best Paper Award for the Virtual Reality Training of Autonomous Vehicle in The 2018 10th International Conference on Modelling, Identification and Control.
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
Püsilink: https://www.kriso.ee/db/97817856132346e.html
Märksõnad: