The Hinf model matching approach to motor tracking control system

The H^∞ model matching algorithm is proposed for the robust motor tracking control of linear time-varying multi-input, single-output uncertain system. This control method is verified by the system of the permanent magnet DC motor to improve the drive performance and reduce sensitivity of parameter variations, nonlinear effects, and other disturbances such as load changes and backlash. The matching model is used to identify the H^∞ tuning controller with bounded noise energy and minimized tracking error. An algorithm based on discrete Ricatti equation and H^∞ interpolation theory is used to solve the uncertain internal modeling and noise measurement issues in the tracking control system. The adaptive tuning controller effectively controls the presence of external disturbances, and identifies the rapid jumping and slow changing trajectory of the system. The effectiveness of the H^∞ model matching controller for the motor tracking control system is demonstrated by using the developed H^∞ adaptive tuning software controller. The H ^∞ model matching control method is examined through computer simulation, and then tested in a real time microprocessor-controlled drive system. Experimental results based on PC based microcomputer implementation are presented to illustrate improved response and robust performance