Abstract—This investigation introduces a novel dual-expert gain scheduling framework for robotic manipulators that is intended to accommodate both abrupt step inputs and steady trajectories in simulation conditions. There are two adaptive controllers that are proposed: the Fuzzy Logic-based Dual Expert Controller (FBDEC) and the Proportional Integral Derivative-based Dual Expert Controller (PBDEC). Each utilizes a classification mechanism that is expert-based in order to dynamically alternate between step and smooth specific gain criteria. PBDEC reduces overshoot to below 9% and obtains up to 47% lower Integral Absolute Error (IAE) and Root Mean Square Error (RMSE) compared to classical Proportional-Integral-Derivative (PID), as evidenced by simulation results on a three-jointed robotic platform. Similarly, FBDEC surpasses conventional fuzzy control by enhancing tracking precision and restricting overshoot to less than 3%. The dual-expert approach, in contrast to traditional single-mode systems, provides a high level of accuracy and a rapid response, seamlessly adapting to a variety of reference profiles. This study delivers the first systematic performance benchmark of PID and fuzzy logic controllers integrated with dual-expert systems across step and smooth inputs, thereby confirming their superiority in terms of generalizability, tracking, and resilience.

Keywords—adaptive control, dual expert control, expert-based gain adjustment, fuzzy logic controller, Proportional-Integral-Derivative (PID) controller, gain scheduling, trajectory classification, robotic manipulator, step input rejection, online rule switching

Cite: Phichitphon Chitikunnan, Panya Minyong, Nuntachai Thongpance, Rawiphon Chotikunnan, Anuchit Nirapai, Pariwat Imura, Wanida Khotakham, Kittipan Roongprasert, and Anantasak Wongkamhang, "Expert-Rule-Based Gain Adjustment for PID and Fuzzy Controllers under Step and Continuous Inputs," International Journal of Mechanical Engineering and Robotics Research, Vol. 14, No. 6, pp. 594-607, 2025. doi: 10.18178/ijmerr.14.6.594-607

Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).