Artificial Intelligence Applied to Control of DC Drives

This paper presents a comparative study and design of various controllers which are used for speed and position control of DC motor. Five controller design strategies and algorithms, especially those using artificial intelligent methods, are introduced and discussed including the conventional control strategies -- root locus and Ziegler-Nichols method, fuzzy logic control, genetic algorithm and a design strategy of on-line tuning of conventional PI controllers. Controllers using above design strategies are employed and simulated in software with test of their transient response and disturbance rejection capability as well as robustness against motor parameter variations. The summaries and comparisons between these controllers with different design strategies are also provided based on a performance index.