A Stable Parameter Area Calculation Method for Advanced Autotuning of a Feedback Controller In highperformance industrial mechatronic servo systems, control parameter tuning is necessary for achieving the desired positioning response to satisfy target control specifications. Autotuning, in particular, is a promising technology for efficient finetuning and is gaining popularity in industrial servo systems. However, finetuning of feedback (FB) control parameters is generally difficult since an aggressive parameter search could lead to the deterioration of control stability. Herein, we present the concept of advanced autotuning method considering a stable parameter area and an efficient calculation method of a stable parameter area to address autotuning of an FB controller. In this paper, the proposed calculation method of a stable parameter area is extended to an FB controller, which comprises a PID controller and some resonant compensation filters, and the calculation time and accuracy are comparatively evaluated with a full searchbased calculation method.

Fuzzy Selftuning Tracking Differentiator for Motion Measurement Sensors and Application in WideBandwidth Highaccuracy Servo Control Sensor differential signals are widely used in many systems. The tracking differentiator (TD) is an effective method to obtain signal differentials. Differential calculation is noisesensitive. There is the characteristics of lowpass filter (LPF) in the TD to suppress the noise, but phase lag is introduced. For LPF, fixed filtering parameters cannot achieve both noise suppression and phase compensation lag compensation. We propose a fuzzy selftuning tracking differentiator (FSTD) capable of adaptively adjusting parameters, which uses the frequency information of the signal to achieve a tradeoff between the phase lag and noise suppression capabilities. Based on the frequency information, the parameters of TD are selftuning by a fuzzy method, which makes selftuning designs more flexible. Simulations and experiments using motion measurement sensors show that the proposed method has good filtering performance for lowfrequency signals and improves tracking ability for highfrequency signals compared to fixedparameter differentiator.