Fault Tolerant Control of Mecanum Wheeled Mobile Robots

TL;DR

This paper introduces a fault tolerant control strategy for Mecanum wheeled mobile robots that effectively manages both complete and partial actuator faults using real-time probabilistic fault estimation, enhancing robustness and safety.

Contribution

It presents a novel FTC approach that incorporates posterior probability to adaptively handle various fault levels in MWMRs, addressing a gap in existing methods.

Findings

Effective fault management demonstrated in simulations

Robust control maintained under diverse fault scenarios

Enhanced safety and performance of MWMRs

Abstract

Mecanum wheeled mobile robots (MWMRs) are highly susceptible to actuator faults that degrade performance and risk mission failure. Current fault tolerant control (FTC) schemes for MWMRs target complete actuator failures like motor stall, ignoring partial faults e.g., in torque degradation. We propose an FTC strategy handling both fault types, where we adopt posterior probability to learn real-time fault parameters. We derive the FTC law by aggregating probability-weighed control laws corresponding to predefined faults. This ensures the robustness and safety of MWMR control despite varying levels of fault occurrence. Simulation results demonstrate the effectiveness of our FTC under diverse scenarios.