Design and Evaluation of a GWO-Assisted Digital Controller for Robotic Manipulators

This paper presents a Self-Adaptive Grey Wolf Optimization-Based Fuzzy Sliding Mode Controller (SAGWO-FSMC) for the nonlinear PUMA 560 manipulator. Initially, fuzzy rules are derived from system characteristics. Then, SAGWO optimizes adaptive membership functions. Comparative analysis with SMC, FSMC, and GWO-SMC shows that SAGWO-FSMC achieves enhanced accuracy and performance over existing control approaches.