Embedded Mechatronics System Design for Uncertain Environments
Linux®-based, Rasbpian®, ARDUINO® and MATLAB® xPC Target Approaches
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 multidisciplinarily 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.
About the Author
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.