Automation and Industrial Computing

Core Courses

The Master's program in Automation and Industrial Computing is an academic two-year training program. The final semester is dedicated to the End-of-Studies Project. The first three semesters include courses organized into Teaching Units (fundamental, transversal, discovery, and methodology). A Teaching Unit consists of one or more subjects taught through lectures, tutorials, practical work, self-study, internships, and projects.

Some of the subjects covered include:

Multivariable Linear Systems:

This course provides a methodology for designing different control laws for multivariable linear systems within the framework of state-space approach.

Signal Processing:

The aim of this course is to master the tools for temporal and frequency representation of analog and digital signals and perform basic processing such as filtering and digital spectral analysis.

Optimization:

Students learn to use complex optimization techniques to improve system performance.

Converter-Machine Association:

This subject explores the different converter-machine associations for rotating electrical machines to control torque and system speed.

Nonlinear Systems:

This course explores the characteristics and control methods of nonlinear dynamic systems.

Embedded Systems and Real-Time Systems:

Students study the principles of design, programming, and management of embedded systems, focusing on the temporal constraints of real-time systems and task synchronization.

Advanced PLC Programming:

This course delves into advanced programming concepts for industrial programmable logic controllers (PLCs), emphasizing advanced applications such as industrial communication, process monitoring, and control.

Applied Electronics:

This course explores advanced aspects of electronics, enabling students to identify and measure electronic components in various systems, including industrial applications.

Advanced Control:

This course trains students to design efficient controllers capable of maintaining high performance levels in the face of various real-world constraints such as parametric un certainties, disturbances, and measurement noise.

Manipulation Robot Control:

This course aims to teach students essential skills in modeling and controlling robotic manipulators. It enables them to gain the autonomy needed to solve various robotics problems, including configuration, trajectory planning, and dynamic control of robots.

Discrete Event Systems:

This course addresses the modeling and control of discrete event systems, characterized by discrete mode changes and specific transitions in their operation.

FPGA and VHDL Programming:

This course focuses on programming Field-Programmable Gate Arrays (FPGAs) using the VHDL (VHSIC Hardware Description Language) for the design and implementation of complex digital electronic systems.

Advanced Topics

The specialization in "Automation and Industrial Computing" trains students to integrate the fields of automatic control and computing in various sectors such as manufacturing, aerospace, land transportation, industrial robotics, healthcare, and mobility.

Additionally, it provides students with the opportunity to compete for LMD doctoral studies in specialized areas such as advanced automation, advanced industrial computing, industrial robotics and robotics, automation of transport and autonomous vehicles, as well as technologies for healthcare and mobility. These specialized topics prepare future doctoral candidates to tackle the complex challenges of modern industry by developing sharp expertise and ethical awareness in the design and implementation of automated and computing systems.