Preparing your Path…
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Path Catalog
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7801 Paths · page 278 / 781
This learning path equips senior engineering students with the skills to design industrial automation systems, covering PLC programming, SCADA, HMI, industrial networks, safety, and embedded systems integration.
This path equips senior and graduate students with the knowledge to apply mechatronics principles to automotive systems, covering engine control, ABS, power steering, and ADAS. It builds from foundational control theory and sensor technology to the analysis and design of integrated automotive mechatronic systems.
This learning path equips learners with the knowledge and skills to apply Hardware-in-the-Loop (HIL) simulation for testing mechatronic systems. It covers foundational control theory, real-time systems, modeling and simulation, and the practical implementation of HIL setups, including test automation and validation.
A focused learning path for junior mechatronics students to master MATLAB and Simulink for modeling, simulation, analysis, and control design. Starting with MATLAB fundamentals, the path builds through programming, Simulink modeling, and control system analysis, culminating in a capstone project.
This graduate-level path develops advanced robotics theory with a focus on mechatronics. It builds from mathematical foundations through manipulator dynamics, motion planning, and force control, culminating in integrated robot control systems.
This graduate-level learning path equips learners with the knowledge and skills to apply nonlinear control techniques to mechatronic systems. It covers foundational mathematical modeling, phase plane analysis, Lyapunov stability theory, and sliding mode control, culminating in practical implementation considerations for mechatronic applications.
This advanced graduate-level path builds a rigorous theoretical foundation for mechatronics, focusing on multi-domain modeling, system dynamics, and analysis. It integrates mechanics, electrical systems, control theory, and numerical methods, culminating in a project-based synthesis.
This learning path guides senior students through the systematic integration and testing of complete mechatronic systems. It covers essential fundamentals, integration planning, interfacing, calibration, and validation, ensuring a holistic understanding of the process.
This advanced learning path equips senior engineering students with the knowledge to apply AI techniques—fuzzy logic, neural networks, machine learning, and expert systems—to mechatronic systems. It bridges foundational mechatronics and control theory with modern intelligent methods, emphasizing practical integration for real-world applications.
This learning path equips senior university students with the knowledge and skills to design advanced embedded systems for mechatronics applications. It covers real-time concepts, RTOS fundamentals, communication protocols, and debugging techniques, building from core microcontroller principles to complex system integration.