This article presents a fault diagnosis control scheme for intrinsically redundant robot manipulators based on the combination of a deep reinforcement learning (DRL) approach and a battery of sliding mode observers. The DRL plays the role of detecting and isolating possible sensor faults, thus generating an alarm and pin-pointing the source. This in turn allows to compensate the sensor faults independently from the actuator ones. The latter are therefore detected and isolated by a set of sliding mode observers driven by input laws designed according to an optimal reaching algorithm. In order to design and apply such observers, a global feedback linearization is performed, which transforms the multi-input-multi-output (MIMO) nonlinear robot model into a chain of double integrators. The proposal is analyzed and assessed in realistic conditions using the PyBullet environment in which a 7 degrees-of-freedom (DOFs) Franka Emika Panda robot manipulator is reproduced.

Sliding mode based fault diagnosis with deep reinforcement learning add‐ons for intrinsically redundant manipulators

Sacchi, Nikolas;Ferrara, Antonella
2023-01-01

Abstract

This article presents a fault diagnosis control scheme for intrinsically redundant robot manipulators based on the combination of a deep reinforcement learning (DRL) approach and a battery of sliding mode observers. The DRL plays the role of detecting and isolating possible sensor faults, thus generating an alarm and pin-pointing the source. This in turn allows to compensate the sensor faults independently from the actuator ones. The latter are therefore detected and isolated by a set of sliding mode observers driven by input laws designed according to an optimal reaching algorithm. In order to design and apply such observers, a global feedback linearization is performed, which transforms the multi-input-multi-output (MIMO) nonlinear robot model into a chain of double integrators. The proposal is analyzed and assessed in realistic conditions using the PyBullet environment in which a 7 degrees-of-freedom (DOFs) Franka Emika Panda robot manipulator is reproduced.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1515102
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 5
social impact