| Subject name (in Hungarian, in English) | Optimal control | |||
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Optimal Control
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| Neptun code | BMEGEMIBMOI | |||
| Type | study unit with contact hours | |||
| Course types and number of hours (weekly / semester) | course type: | lecture (theory) | exercise | laboratory excercise |
| number of hours (weekly): | 2 | 1 | 0 | |
| nature (connected / stand-alone): | - | coupled | - | |
| Type of assessments (quality evaluation) | mid-term grade | |||
| ECTS | 3 | |||
| Subject coordinator | name: | Dr. Budai Csaba (73554263569) | ||
| post: | adjunct | |||
| contact: | budai@mogi.bme.hu | |||
| Host organization | Department of Mechatronics, Optics and Mechanical Engineering Informatics | |||
| http://www.mogi.bme.hu/ | ||||
| Course homepage | http://www.mogi.bme.hu/tantargyak/BMEGEMIBMOI | |||
| Course language | english | |||
| Primary curriculum type | mandatory | |||
| Direct prerequisites | Strong prerequisite | BMEGEMIBMRI | ||
| Weak prerequisite | ||||
| Parallel prerequisite | ||||
| Milestone prerequisite | at least obtained 0 ECTS | |||
| Excluding condition | none | |||
Aim
Methods for testing and describing linear systems in a time domain. Stability test. Introduction to the loop-shaping controller design method. Description of the integrator antiwindup technique used in engineering practice, compensation of the effect of dead time. Presentation of optimal controller design and model predictive control. Discuss and apply the main model identification techniques to produce linear models based on measured data.
Learning outcomes
Competences that can be acquired by completing the course
Knowledge
Knows basic control engineering tasks and the general structure of regulatory circuits. Knows the most important tuning methods of P, PI, PD, PID controllers. Interprets the application possibilities of the loop-shaping method for the design of a PID controller. The student knows the concept of integrator anti-windup, dead time, Pade approximation, and Smith predictor. It interprets the method of lead-lag control technique. The student is aware of the concepts of status feedback, setpoint compensation, and load estimation. Informed about the LQR optimal state feedback method. The student is aware of the working principle of model predictive control. Informed about the concept and use of Riccati equations. The student is familiar with basic model identification techniques.
Ability
Able to design control circuits with unstable poles. It examines the impact of dead time on PID controllers during design. It designs the PID controller taking into account the dead time effect. It designs the PID controller using an integrator antiwindup. Apply the Pade approximation to approximate the dead time term. Apply the lead-lag control design procedure. Capable of designing PID controllers considering robustness criteria using loop-shaping. Plans LQR optimal state feedback. Apply the model predictive technique to control design. Capable of LTI model identification based on measurement data.
Attitude
The student constantly monitors his work, results, and conclusions. It expands your knowledge of control technology by continuously acquiring knowledge. Open to the use of information technology tools. It develops the ability to provide accurate and error-free problem solving and engineering precision. It seeks to learn about novel theories of control technology.
Independence and responsibility
Collaborates with the instructor and fellow students to expand knowledge. Accepts well-founded professional and other critical remarks. In some situations, as part of a team, you work with your fellow students to solve tasks. With his knowledge, he makes a responsible, well-founded decision based on his analyzes. The student is committed to the principles and methods of systematic thinking and problem-solving.
Teaching methodology
During the teaching of the subject, the lecture and the classroom practice are separated in methodology. The lectures basically introduce students to the information defined by the knowledge competence elements using the technique of frontal education. The practical sessions promote the application and skill-level acquisition of knowledge with a theme coordinated with the lectures, but with the mirrored classroom method. During the exercises, the knowledge previously acquired at home, independently, is solved partly jointly and partly individually with the help of the practice leader. In order to assess prior knowledge, there are optional assessments at the beginning of the practical sessions, the results of which (as extra points) are included in the semester score.
Support materials
Textbook
Katsuhiko Ogata: Modern Control Engineering. Pearson, 2011, ISBN-13: 978-0136156734
Lecture notes
Online material
Validity of the course description
| Start of validity: | 2022. May 15. |
| End of validity: | 2026. July 15. |
General rules
The assessment of mid-year learning outcomes consists of 2 compulsory and 1 optional mid-year performance measures. The condition for obtaining the mid-term grade is to achieve a result of at least 40% in the summary performance evaluation and the partial performance evaluation, respectively. With the active participation in the classroom practical sessions (optional mid-year performance measurement), additional points can be obtained, which can be included in the grade if at least a sufficient mid-year grade is obtained.
Assessment methods
Detailed description of mid-term assessments
| Mid-term assessment No. 1 | ||
| Type: | summative assessment | |
| Number: | 1 | |
| Purpose, description: | Summarizing academic performance evaluation is a complex, written way of evaluating the knowledge and ability type competence elements of the subject in the form of an indoor dissertation. The dissertation basically focuses on the application of the acquired knowledge, so it focuses on problem recognition and solution solution, ie practical (calculation) tasks must be solved during performance evaluation. The condition for the sufficient completion of the dissertation is to achieve a result of at least 40%. | |
| Mid-term assessment No. 2 | ||
| Type: | formative assessment, simple | |
| Number: | 1 | |
| Purpose, description: | Partial performance assessment (homework) is a complex way of evaluating the knowledge, ability, attitude, as well as independence and responsibility type competence elements of the subject, the form of which is the individual homework. The condition for the sufficient completion of homework is to achieve a result of at least 40% separately, taking into account the observance of the pre-specified formal requirements. Pursuant to Section 122 (2) of the BME TVSZ, the value of the available score decreases by 20% per homework during late submission. | |
| Mid-term assessment No. 3 | ||
| Type: | formative assessment, point-in-time personal act | |
| Number: | 1 | |
| Purpose, description: | Partial performance assessment (active participation) is a simplified way of assessing the knowledge, ability, attitude and autonomy and responsibility type competence elements of the subject, the form of which is: prepared appearance and active participation in the classroom and laboratory practice process, on-demand example solution for students, solving an optional diligence task or writing optional control tests. Due to its nature, active participation cannot be replaced, improved, or otherwise replaced or replaced. | |
Detailed description of assessments performed during the examination period
The subject does not include assessment during the examination period.
The weight of mid-term assessments in signing or in final grading
| ID | Proportion |
|---|---|
| Mid-term assessment No. 1 | 60 % |
| Mid-term assessment No. 2 | 40 % |
| Mid-term assessment No. 3 | 15 % |
The condition for signing is that the score obtained in the mid-year assessments is at least 40%.
The weight of partial exams in grade
There is no exam belongs to the subject.
Determination of the grade
| Grade | ECTS | The grade expressed in percents |
|---|---|---|
| very good (5) | Excellent [A] | above 90 % |
| very good (5) | Very Good [B] | 85 % - 90 % |
| good (4) | Good [C] | 70 % - 85 % |
| satisfactory (3) | Satisfactory [D] | 55 % - 70 % |
| sufficient (2) | Pass [E] | 40 % - 55 % |
| insufficient (1) | Fail [F] | below 40 % |
The lower limit specified for each grade already belongs to that grade.
Attendance and participation requirements
The lack of the value means that there is no attendance requirement.
At least 70% the exercises (rounded down) must be actively attended.
Special rules for improving, retaken and replacement
The special rules for improving, retaken and replacement shall be interpreted and applied in conjunction with the general rules of the CoS (TVSZ).
| Need mid-term assessment to invidually complete? | ||
| yes | ||
| Can the submitted and accepted partial performance assessments be resubmitted until the end of the replacement period in order to achieve better results? | ||
| NO | ||
| The way of retaking or improving a summary assessment for the first time: | ||
| each summative assessment can be retaken or improved | ||
| Is the retaking-improving of a summary assessment allowed, and if so, than which form: | ||
| retake or grade-improving exam not possible | ||
| Taking into account the previous result in case of improvement, retaken-improvement: | ||
| out of multiple results, the best one is to be taken into account | ||
| The way of retaking or improving a partial assessment for the first time: | ||
| partial assesment(s) in this group can be improved or repeated once up to the end of the repeat period | ||
Study work required to complete the course
| Activity | hours / semester |
|---|---|
| participation in contact classes | 42 |
| mid-term preparation for practices | 7 |
| preparation for summary assessments | 16 |
| elaboration of a partial assessment task | 4 |
| additional time required to complete the subject | 21 |
| altogether | 90 |
Validity of subject requirements
| Start of validity: | 2022. May 15. |
| End of validity: | 2026. July 15. |
Primary course
The primary (main) course of the subject in which it is advertised and to which the competencies are related:
Mechatronics engineering
Link to the purpose and (special) compensations of the Regulation KKK
This course aims to improve the following competencies defined in the Regulation KKK:
Knowledge
- Student has the knowledge of the tools and methods for mathematical modelling and computer simulation of integrated mechanical, electrical and control systems in the various fields of mechatronics.
Ability
- Student has the ability to develop independently the theoretical knowledge and to apply new theory to the practical solution of complex mechatronic design problems of an unconventional nature.
Attitude
- Based on student's acquired knowledge, Student plays an integrative role in the integrated application of engineering disciplines (in particular mechanical, electrical and computer engineering) and in the technical support of all disciplines where engineering applications and solutions are required by professionals in the field.
Independence and responsibility
- Student takes the initiative in solving technical problems.
Prerequisites for completing the course
|
Knowledge type competencies
(a set of prior knowledge, the existence of which is not obligatory, but greatly facilitates the successful completion of the subject) |
none |
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Ability type competencies
(a set of prior abilities and skills, the existence of which is not obligatory, but greatly contributes to the successful completion of the subject) |
none |