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This paper presents a novel auto-tuning subsystem-based fault-tolerantcontrol (SBFC) system designed for robot manipulator systems with n degrees offreedom. It first employs an actuator fault model to account for various faultsthat may occur, and second, a mathematical saturation function is incorporatedto address torque constraints. Subsequently, a novel robust subsystem-basedadaptive control method is proposed to direct system states to follow desiredtrajectories closely in the presence of input constraints, unknown modelingerrors, and actuator faults, which are primary considerations of the proposedsystem. This ensures uniform exponential stability and sustained performance.In addition, optimal values are identified by tuning the SBFC gains andcustomizing the JAYA algorithm (JA), a high-performance swarm intelligencetechnique. Theoretical assertions are validated through the presentation ofsimulation outcomes.

Exponential Auto-Tuning Fault-Tolerant Control of N Degrees-of-Freedom Manipulators Subject to Torque Constraints