DC motor control via high order differential feedback control

In practice, there are many motor systems whose models are usually unknown or partially unknown. However, the majority of control schemes focus on model-dependent techniques. To cope up with unavailable dynamics, a model-free controlling problem for a DC motor system is investigated in this study. A robust higher-order differential feedback controller (HODFC), which does not depend on the model of the controlled DC motor system, is applied. The controller only utilizes the information of the measured output and the given objective as well as the extracted differentials of those via higher-order differentiator (HOD). Simulation results show that HODFC successfully controls the uncertain DC motor system, and can drive its trajectories to desired steady states subject to unknown bounded disturbance. Stability, convergence and robustness of PID, fuzzy and HODFC control schemes for the closed-loop system behavior are compared. From the performance comparisons, the robust HODFC control system yields favorable control performance superior to that of PID and fuzzy control systems. Moreover, it not only has a learning ability similar to that of fuzzy control but also a simple control structure as PID control.