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IK4 Doctorados

 

IKERLAN

Research aimed at the development of people  and transfer of the most advanced technologies for companies.

 
DOCTORATES

IKERLAN

Development of control algorithms and Machine Learning Control techniques for mechatronic systems

IKERLAN

START: 09/2018

OPEN

OBTAINING DOCTOR DEGREE: 09/2021

Description

The PhD work offered is located in the Advanced Control specialization team belonging to the Control and Monitoring knowledge area. The team"s research line focuses on the dynamic modelling of mechatronic systems and the design and implementation of advanced solutions for the control of these systems. Most of the projects usually cover the whole development chain, starting from the modelling of the system to be controlled, through the design of the algorithms, their verification by means of simulations, their implementation in electronic devices and their validation by means of HIL (Hardware In the Loop) techniques first and in the field or machine at the end.

In the work proposed for the development of the thesis, the team of IK4-Ikerlan proposes the development and validation by means of simulation of control algorithms dedicated to optimizing the performance of the system in order to find the best balance between dynamic performance, availability against failures and efficiency in resources such as consumption.

Although it is an eminently transversal technology, in recent years and under the impulse of two agreements of collaboration with tractor companies, the Ikerlan team has specialised mainly in two fields: Industry 4.0 (including Collaborative Robotics) and Wind Energy, in which Ikerlan is a state and European benchmark with participation in important projects and with top-level publications.

The development of the thesis will be carried out in collaboration and coordination with some of the leading companies in the field, replicating the thesis model that the Advanced Control specialization group has practiced successfully in recent years in the hands of industrial partners.

On the basis of the background of the team and taking advantage of the proximity to one of the relevant industrial agents, it is estimated that the objectives established in the thesis can be achieved in three years of work. As it has already happened in previous cases, cooperation with companies throughout the thesis can also facilitate the continuity of the doctoral student in IK4-Ikerlan in order to deepen the transfer of the knowledge acquired to industrial use and development cases.

In a generic way, throughout the thesis an approach to the following phases in chronological order is proposed:

  • Study of the state of technology: Theses, articles and patents published to date will be analysed in order to know the current state of this technology and to be able to propose new lines of research throughout the thesis work. This work can even be very useful to strengthen the selection of the scope of application.

 

  • Dynamic modelling of systems: In a preliminary phase, the different options available for modelling and simulation of the system to be studied will be analysed. Depending on the field of application (wind, Industry 4.0 or collaborative robotics), the tools may be different, from generic use such as Matlab/simulink or OpenModelica, to specific tools such as OpenFast for wind turbines.
  • Development of basic control algorithms: In this phase, a basic controller will be developed that will be used as a benchmark for future advanced strategies. For this, a SW structure compatible with the selected simulation tool will be established and the most common control loops will be implemented in this type of systems. A first tuning of said loops will be carried out in order to have a stable operation throughout the entire operating range of the machine.
  • Development of advanced control algorithms: It is the central phase of the thesis work. A set of specific loops and controllers will be designed to optimise the performance of the mechatronic system. The control problem can also be raised from a multivariable integral vision. In this way, different control objectives can be addressed simultaneously in order to achieve a balance between them. A possible approach would involve the application of robust control algorithms known in detail by the IK4-Ikerlan research group.
  • The validation of the control loops developed will be done by simulation batteries according to the operation cases. To do this, the full non-linear models developed in the previous phase will be used.
  • Optimization of the tuning of the controllers: The approach to the tuning problem is usually approached according to the set of linear plans that represent the system throughout the entire range of operation. This can lead to a lack of reliability in the results obtained, as the linear models offered by the modelling tools are not precise and do not represent the effects of the operational and external perturbations such as waves. In this thesis, it is proposed to investigate and develop new methodologies for the design and tuning of controllers taking into account optimization solutions according to the new trends of Machine Learning Control.
  • Application of advanced algorithms developed to a commercial system: In this last phase of the work it is proposed to apply the most promising set of algorithms to a commercial system or in the process of being commercialised by one of the benchmark companies in the sector.

Department or unit of the Associates Technology Center

Advanced Manufacturing

Investigation line

Advanced Control

Start date planned

09/2018

Obtaining date of the doctor degree

09/2021

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