The Institute is mainly concerned with

1. System Analysis and Modelling

1.1. Model Structure - Representation basis
  • Compact representation of nonlinear systems
  • Quadratic extensions of bilinear forms
  • Extended State Affine Systems
  • StructureIdentification 

1.2. Parameter estimation for nonlinear Systems

  • Subspace identification of extended state affine systems
  • LPV and NLPV models
  • Iterative identification of polynomial NARX models
  • Adaptive LMS estimation
 1.3.  Data Based system analysis
  • Fault-detection and analysis of complex systems
  • Data driven causality analysis
  • Learning fault detection architecture for unknown systems
  • Iterative model-on-demand approach for fault diagnosis in engine systems
2.     Control

2.1   Optimal control of nonlinear systems

  • Optimal approximate control of non-input affine nonlinear systems
  • Approximate optimal control: Solution of the HJB problem via multimodel policy iteration
  • Approximate optimal control: Iterative solution of the discrete time HJB
  • Approximate optimal control: Solution of the HJB under input constraints
  • Model predictive control
2.2   Tracking and rejection for nonlinear systems
  • Rejection of quasi peridic disturbances
  • Iterative learning control with time constraints
  • Generation of trajectories for control from specifications
  • Control of multiple agents

3.       Applications

3.1 Automotive

  • Internal combustion engine test benches
  • Multi agent systems

3.2 Medical applications

  • Glucose control
  • Monitoring

3.3 Industrial applications

  • Drives and actuators
  • Steel industry
  • Elevator
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