Important notice
The course guide is provisional.
The PDF version of the course guide may take a few days to become available in the DDD.

Cyberphysical Systems
Code: 44732Credits: 6
| Degree programme | Type | Course |
|---|---|---|
| Research and Innovation in Computer based Science and Engineering | OP | 1 |
Contact lecturer
- Name :
- David Castells Rufas
- Email :
- david.castells@uab.cat
Group languages
You can consult this information at the end of the document.
Prerequisites
Basic Python programming skills
Objectives
The objective of the subject is to train students to be able to design computating systems that are integrated into processes that interact with the physical world.
- Learn to model and analyze the behaviour of the physical world
- Learn to design control systems
- Propose control systems and create simulation environments to evaluate their characteristics
- Create control systems that interact with the physical world in real time
Learning outcomes
- CA08 (Design innovative applications in the fields of science and engineering by applying solutions theoretical models and using techniques and tools based on cyber-physical systems.) Design innovative applications in the fields of science and engineering by applying solutions theoretical models and using techniques and tools based on cyber-physical systems.
- CA09 (Analyse research results to obtain new products or processes based on cyber-physical systems, and assess their industrial and commercial viability for their transfer to society.) Analyse research results to obtain new products or processes based on cyber-physical systems, and assess their industrial and commercial viability for their transfer to society.
- KA12 (Describe the principles, functions and attributes of cyber-physical systems, embedded systems and the Internet of Things (IoT) paradigm, as well as identify the specifications and performance metrics of the different cases.) Describe the principles, functions and attributes of cyber-physical systems, embedded systems and the Internet of Things (IoT) paradigm, as well as identify the specifications and performance metrics of the different cases.
- KA13 (Describe the operation of sensing, connection and cognition features; sensors, actuators, computation and communication protocols; modelling, analysis and tools.) Describe the operation of sensing, connection and cognition features; sensors, actuators, computation and communication protocols; modelling, analysis and tools.
- SA14 (Solve problems that require elements of the IoT value chain in order to implement cyber-physical systems by structuring the tasks at each level (device, periphery, cloud), and selecting appropriate technologies and tools.) Solve problems that require elements of the IoT value chain in order to implement cyber-physical systems by structuring the tasks at each level (device, periphery, cloud), and selecting appropriate technologies and tools.
- SA15 (Design the optimal solution for specific cyber-physical systems based on cost-performance criteria (real time and energy efficiency) and using sensors and actuators, embedded and real or virtual mobile platforms, for both computing and communication.) Design the optimal solution for specific cyber-physical systems based on cost-performance criteria (real time and energy efficiency) and using sensors and actuators, embedded and real or virtual mobile platforms, for both computing and communication.
- SA16 (Develop project solutions in the different fields of cyber-physical systems taking into account aspects of multidisciplinary co-design, privacy and data security.) Develop project solutions in the different fields of cyber-physical systems taking into account aspects of multidisciplinary co-design, privacy and data security.
- SA17 (Select information from the scientific literature using the appropriate channels, then integrate this information using synthesis and debate skills and analyse any viable alternatives.) Select information from the scientific literature using the appropriate channels, then integrate this information using synthesis and debate skills and analyse any viable alternatives.
Contents
- Introduction to cyber-physical systems and applications
- Modeling of continuous dynamics systems
- Modeling of discrete systems
- Computing models (dataflow, state machines, etc.) and hybrid systems
- Systems simulation
- Embedded computing platforms
- Control algorithms
- Platform development and integration
- Project presentation
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Discussion and laboratory sessions | 24 | 0.96 | KA13, SA14, SA15, SA16 |
| Theory classes | 26 | 1.04 | CA09, KA13, SA17 |
| Project development | 80 | 3.2 | CA08, SA14, SA15, SA16 |
Theory classes:
Presentations on the board of the theoretical part of the subject syllabus. The basic knowledge of the subject is presented and instructions on how to complete and deepen the materials.
Project development:
The scientific and technical knowledge presented in the master classes is worked on in the context of challenges to implement specific cyber-physical systems. The challenges will be worked on iteratively in discussion seminars with the teacher as well as with laboratory sessions where the implementation will be carried out on the final execution platform. Students will have to make several presentations in the class as they progress in defining their project and will have to deliver the presentation made during the class through the virtual campus. In these sessions and the development sessions in the laboratory, the ability to analyze and synthesize, critical reasoning is promoted, and the student is trained in communicating results and solving problems.
Use of AI:
For this subject, the use of Artificial Intelligence (AI) technologies is permitted exclusively in support tasks, such as bibliographic or information searches, text correction or translations. The student must clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how these have influenced the process and the final result of the activity.
The lack of transparency in the use of AI in this assessable activity will be considered a lack of academic honesty and may lead to a partial or total penalty in the grade of the activity, or greater sanctions in serious cases.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Laboratory work | 40% | 10 | 0.4 | CA09, KA12, KA13, SA14, SA15, SA17 |
| Presentations in class | 60% | 10 | 0.4 | CA08, CA09, KA12, KA13, SA14, SA15, SA16, SA17 |
This subject does not provide for the single assessment system.
The assessment will be carried out by continuous assessment on the presentations made in class and also delivered through the virtual campus. At least 3 presentations will be made. In these presentations the student will defend the evolution of his project, both in the conceptual field and the work done in the laboratory. The continuous evaluation mark will be calculated as an average of the score obtained in each of these installments.
Attendance at the laboratory sessions is mandatory and there is no mechanism established for the recovery of sessions not attended. In case of not attending more than 50% of laboratory sessions, the subject will be suspended with a final grade proportional to the number of sessions attended.
Evaluation Considerations:
- The subject is considered non-evaluable when no presentation has been taken and no more than two laboratory sessions have been held.
- Awarding an honors matriculation qualification is the decision of the teaching staff responsible for the subject. UAB regulations indicate that MH can only be granted to students who have obtained a final grade equal to or higher than 9.00. Up to 5% of MH of the total number of enrolled students can be awarded.
- In case of not passing the subject by continuous assessment and having attended the minimum number of laboratory sessions, the student may take a final exam on the subject given in all the activities of the course.
- Without prejudice to other disciplinary measures that are deemed appropriate, and in accordance with current academic regulations, irregularities committed by a student that may lead to a variation of the grade will be graded with a zero (0). For example, plagiarizing, copying, allowing copying, ..., an assessment activity, will involve failing this assessment activity with a zero (0). Assessment activities qualifiedinthis way and by this procedure will not be recoverable. If it is necessary to pass any of these assessment activities to pass the subject, this subject will be failed directly, without the opportunity to recover it in the same course.
Bibliography
- Lee, Edward Ashford, and Sanjit Arunkumar Seshia. Introduction to embedded systems: A cyber-physical systems approach. MIT press, 2016.
Software
Ptolemy II (free)
Arduino IDE (free)
Python 3 + Jupyter Notebook (free)
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TEm) Theory (master) | 1 | English | first semester | afternoon |
| (PLABm) Practical laboratories (master) | 1 | English | first semester | afternoon |