Active research in system theory, complex systems, adaptive and learning control along with soft computing is carried out in the laboratory, with special emphasis on structural theory and time-varying linear systems, time-delay systems, neural networks and fuzzy computing.
Analysis of system identifiability. New measures for numeric visibility and excitability of model parameters have been defined; these tools have been exploited to construct more robust identification algorithms.
Combination of computability theory with dynamic system theory. It has been shown that any algorithm can be coded as a simple discrete-time nonlinear system. The results from computability theory (undecidability issues, etc.) can thus be extended to analysis of dynamic systems.
Structural analysis of multivariable linear time-vaying differential systems. Pole sets, system zeros, stability and performance.
- Polynomial systems
- Time-varying systems
- Non-standard parameterizations
- Identification and identifiability
- Adaptive control
- PID control tuning
- Time-delay and distributed parameter systems
Soft computing methods
- Neural networks
- Fuzzy systems
- Evolutionary computing / Markov chain analysis
- Bio-influenced computing
- Global optimization methods
- Structure in processes
- Statistical methods
- Artificial intelligence and models of cognition