Fixed Point Iteration-Based Adaptive Control Improved with Parameter Identification

This paper reports the freshest element of the chain of investigations tackling the combination of the Fixed Point Iteration-based adaptive controller with parameter identification. Though this controllers does not necessarily use the identified model, it is expected that the use of the more precise model improves its various properties. Simulation investigations are made for a cylindrical robot for replacing the Particle Swarm Optimization with simple regression-based approach. It is concluded that the use of the best identified model still makes it expedient the application the FPI-based adaptivity. The remaining imprecisions seem to be related to the not well balanced structure of the experimentally collected and analyzed data. It can be expected that this approach can be realized real-time with appropriate hardware.