Fuzzy inference-based on-line control gain tuning for servo drive system

This paper presents a novel fuzzy inference based on-line control gain tuning for servo drive system which is modeled as a 1-mass system. The proposed fuzzy inference system identifies a system moment of inertia and adjusts control gains by using the difference in speed responses between a real plant and a reference model. In the paper, a simple tuning algorithm for online processing and design of the fuzzy membership function are especially examined to attain the practical online tuning. To achieve the effective tuning algorithm, the simplified inference process which is constituted by a simple equation is derived. In addition, the practical design procedure for the membership function based on the inference principle is systematized. The proposed algorithm is verified by experiments using a prototype. In the experiments, the system moment of inertia is identified and the control gains are autonomously adjusted with the specified tuning accuracy and, as a result, desired speed and position responses are obtained.