A Novel PID Robotic for Speed Controller Using Optimization Based Tune Technique

One of the most significant issue of proportional integral derivative (PID) controller is the efforts to optimize coefficient gains. Based on survey, massive tuning methods were proposed to resolve this problem but there is little pay attention to maximize minimization time response significantly. This study proposed a novel technique to maximize optimization PID gains for the DC motor controller by combining both proper tuning method with signal input signal output (SISO) optimization toolbox using optimization based tune (OBT) techniques, that could be utilized for the highest precision controller. The comparative study has been carried out by applying five different tuning methods to obtain a proper tuning controller, then to be combined with SISO optimization toolbox. The utilized tuning methods are Robust Auto tune (RAT), Ziegler–Nichols (Z-N), Skogestad Internal Model Control (SIMC), Chien Hroues Reswick (CHR), and Approximate M-Constrained Integral Gain Optimization (AMIGO). The performance of each tuning methods based OBT are analyzed and compared using MATLAB/SISO tool environment, where the efficiency has been assessed on a basis of time response characteristics (Ti) in terms of dead time (td), rise time (tr), settling time (ts), peak time (tp) and peak overshoot (Pos). The simulation results of AMIGO based proposal show a significant reduction time response characteristic to be measured in the Microsecond unit (μs). The novelty feature of the proposed is that provides superior balancing between robustness and performance. This study has been completely rewritten to account for the robotic controller development that has been taken place in the last years.