Adaptive Control for A General Class of Switched Reluctance (SR) Motor ModelsThe SR motor is basically an ac machine with an iron core rotor, i.e., there are no mechanical brushes that require expensive maintenance as are required with the permanent magnet, brushed dc motors. There are several advantages to using the SR motors as actuators in high performance motion control applications. These advantages include their low cost and high reliability through simple design and construction, increased capability to withstand high temperature environments, significant reduction in friction, and their ability to increase torque production through electromagnetic gearing. Since the SR motors are often utilized in applications requiring high torque, the motor is often operated "high" on the saturation curve; hence, many motor control experts believe that saturation effects must be included in the SR motor model. The flux linkage model determines the complexity of the SR motor electromechanical dynamics. That is, at least in principle, standard calculations can be applied to the flux linkage model to complete the description of the electrical subsystem dynamics and the algebraic torque transmission relationship. based on this fact we have utilized a very general, nonlinear model of the SR motor to develop an adaptive backsteppingtype controller for the fullorder electromechanical model.To illustrate the generality of the approach, we show how the controller remains valid for a proposed flux linkage model which attempts to account for the magnetic saturation effects. An experiment was conducted to test the performance of the proposed controller. A very heavy inertial load was built inhouse (See Figure 1) so that the motor operates "high" on the saturation curve. The fluxlinkage relationship was modeled using an arctangent function. The comparison between linear fluxlinkage model and the actual fluxlinkage along with the arctangent approximation is shown in Figure 2. The performance of the saturated fluxlinkage model based controller with the linear flux linkage model based controller as quantified by their respective position tracking errors is shown in Figures 3 and 4. Figure 1: Experimental Setup Used
