A Tutorial on Dynamic Simulation of DC Motor and Implementation of Kalman Filter on a Floating Point DSP

With the advent of inexpensive 32 bit floating point digital signal processor’s availability in market, many computationally intensive algorithms such as Kalman filter becomes feasible to implement in real time. Dynamic simulation of a self excited DC motor using second order state variable model and implementation of Kalman Filter in a floating point DSP TMS320C6713 is presented in this paper with an objective to introduce and implement such an algorithm, for beginners. A fractional hp DC motor is simulated in both Matlab and DSP and the results are included. A step by step approach for simulation of DC motor in Matlab and “C” routines in CC Studio is also given. CC studio project file details and environmental setting requirements are addressed. This tutorial can be used with 6713 DSK, which is based on floating point DSP and CC Studio either in hardware mode or in simulation mode. Keywords—DC motor, DSP, Dynamic simulation, Kalman Filter. NOMENCLATURE Rm Armature resistance in Ohms; Lm Inductance in mH, Kb Back EMF constant (Volt-sec/Rad) Kt Torque constant (Nm/A) Jm Rotor inertia (Kg m ) Bm Mechanical damping factor Kk Kalman gain Pk Posterior co-variance ( ) P k − Prior co-variance Q State noise R Measurement noise.