Modeling, Analysis and Monitoring DC Motor Using Proportional-Integral Controller and Kalman Filter

This paper presents a method for monitoring control systems having output that is disturbance-free and noisy output. As a model-based fault detection scheme, a good knowledge of the control system is a necessity hence the DC motor used as the control system here was first modeled as an ideal DC motor. To ensure the stability of the speed control DC motor, Lyapunov stability test for linear time invariant system is done while bode plot was used to confirm the asymptotic stability of the DC motor. Then PI controller is designed rule for stability and set point tracking using Ziegler Nichols tuning method. Motivated by this, a Kalman filter is designed for state estimation of the noisy DC motor. The healthy and faulty DC motor outputs are then compared. Large deviation exists indicating the presence of fault. Simulation results show the DC Motor attaining steady state of 34 rev/s speed which also agrees with theoretical calculation. Also the fault detection method was able to identify incipient faults in the DC motor.