In the winter semester 2017L I teach the following courses:
- Modelling and Identification (MODI) in Polish: exercises.
- M.Sc. Seminar 2 (SDM2).
B.Sc. M.Sc. and Ph.D. theses
B.Sc. and M.Sc. theses
In general, I superivise B.Sc. and M.Sc. theses which fall into the following four categories:
- Software works, e.g. development of a software system that makes it possible to solve a typical engineering problem, utility software or a specialised toolbox for Matlab.
- Research works in the field of automatic control, e.g. implementation, comparison and possible improvement of some existing control algorithms, in particular model predictive control algorithms.
- Research works in the field of artificial intelligence and soft computing (neural networks, fuzzy systems, evolutionary algorithms). Applications of artificial intelligence and soft computing in process control.
- Practical works in the field of automatic control, i.e. practical implementation of some control algorithms for laboratory or industrial processes.
Currently available B.Sc. theses:
- Laboratory magnetic levitation process: modelling, identification, control and visualisation.
- Laboratory servo: modelling, identification, control and visualisation.
- Implementation of neural networks in computer network environment.
- Internet-based simulator of model predictive control algorithms.
- Comparison of classical and advanced control algorithms for a multivariable process.
- Comparison of three model predictive control algorithms for a multivariable process.
- Computationally efficient implementation of particle swarm optimisation algorithms - application to neural network training.
Currently available M.Sc. theses:
- Laboratory crane: modelling, identification, control and visualisation.
- Laboratory helicopter: modelling, identification, control and visualisation.
- Laboratory heating and ventilation process: modelling, identification, control and visualisation.
- In search of the best structure of a neural network: from the classical approaches to the soft computing methods.
- Neural networks in model predictive control algorithms.
- Genetic programming as a method of models synthesis for predictive control.
- Computationally efficient model predictive control algorithms based on state-space models.
- Structure selection and training of neural networks using large data sets.
- Development of a software system for fast prototyping of control algorithms for microcontrollers.
The subjects of theses given above are only examples. I encourage students to suggest their own subjects or fields of research. The subjects of many B.Sc. and M.Sc. theses completed under my supervision were suggested by their authors. Please contact me in order to discuss the details.
I encourage the students who currently graduate (or graduates) to take up Ph.D. studies. In particular, I encourage the people who:
- Want to work in the great field of science.
- Are interested in the field of process control, computer science and artificial intelligence (soft computing).
- Want to learn how to efficiently work in a group.
- Want to participate in interesting research as well as in research and development projects.
- Want to learn how to present the results of their works during scientific conferences and in journal articles.
The subject and the scope of the Ph.D. thesis may be formulated by the supervisor. However, it is much more beneficial when they are suggested by the Ph.D. student herselft/himself after completing a few preliminary projects which show different possible research directions in process control, computer science and soft computing. Please contact me in order to discuss the details.