Nonlinear closed-loop direct identification of a DC motor with load for low speed two-directional operation

Identification of systems operating in closed loop has been of primary concern in many industrial applications and scientific research for the last few decades. Control engineering has been one of the major fields of application of system identification in closed loop. DC motors are widely used in control systems as actuating elements or parts of the plant to be controlled. Major nonlinearities affecting the behavior of a motor and its load take effect especially at low speeds and during reversal of direction. The purpose of the current contribution is to present a nonlinear direct approach to the identification of a DC motor with load in closed loop, and show that the suggested nonlinear direct approach significantly reduces the error caused by the nonlinear effects at certain time intervals. The nonlinear model was built utilizing a Hammerstein system structure. The linear approach and the suggested nonlinear approach are tested via real time experiments and results are graphically presented. The accuracy of the suggested method is also revealed by graphics and tabulated data.