From experiment design to closed-loop control

From experiment design to closed-loop control

The links between identification and control are examined. The main trends in this research area are summarized, with particular focus on the design of low complexity controllers from a statistical perspective. It is argued that a guiding principle should be to model as well as possible before any model or controller simplifications are made as this ensures the best statistical accuracy. This d...

Experiment Design for Closed-loop Performance Diagnosis ⋆

This paper uses prediction error identification to distinguish control-relevant system changes in closed-loop operation from variations in disturbance characteristics. The approach consists of a hypothesis test to verify whether an identified model of the true system lies in a set containing all models that exhibit adequate closed-loop performance. To increase the detection probability, i.e. th...

Optimal Experiment Design in Closed Loop

In this contribution we extend a recently developed framework for open loop input design to closed loop experiment design. More specifically, for the very common situation of a fixed controller during the identification experiment, the framework is extended to the design of an optimal reference signal spectrum and also to cope with closed loop signal constraints. In a further extension also the...

Learning open-loop from closed-loop control

This paper explores an evolution from closed-loop control to open-loop control for a planar manipula-tor. A reinforcement learning strategy is used to learn the open-loop commands from the closed-loop control. The goal is to produce a motion using purely open-loop control strategy, thereby eliminating the need for inter-link communication and on-line control computations. Initially closed loop ...

On Application Oriented Experiment Design for Closed- loop System Identification