This article presents a robust adaptive neural network controller for switched reluctance motor (SRM) speed control with both parameter variations and external load disturbances. The radial basis function neural network with the technology of minimal learning parameters is employed to approximate an ideal control law which includes the parameter variations and external disturbances. Furthermore, a proportional control term is introduced to improve the transient performance and chattering phenomena of the SRM drive system. The asymptotic stability of the proposed controller is guaranteed through rigorous Lyapunov analysis. A main advantage of the proposed control scheme is that it contains only one adaptive parameter that needs to be updated on-line. This advantage result in a much simpler adaptive control algorithm, which is convenient to implement in switched reluctance drives. Finally, the simulations and experiments are carried out to demonstrate the effectiveness of the proposed control scheme.

This paper proposes a high-performance indirect control scheme for torque ripple minimization in the switched reluctance motor (SRM) drive system. Firstly, based on the nonlinear torque-angle characteristic of SRM, a novel torque sharing function is developed to obtain the optimal current profiles such that the torque ripple is minimized with reduced copper losses. Secondly, in order to track current accurately and indirectly achieve high-performance torque control, a robust current controller is derived through the Lyapunov stability theory. The proposed robust current controller not only considers the motor parameter modeling errors but also realizes the fixed frequency current control by introducing the pulse width modulation method. Further, a disturbance-observer-based speed controller is derived to regulate the motor speed accurately, and the load torque is considered an unknown disturbance. The simulations and experiments on a 1.5 kW SRM prototype are carried out to demonstrate the effectiveness of the proposed high-performance indirect torque control strategy. Results verify the superiority of the proposed strategy with respect to the torque ripple suppression, system efficiency, and antidisturbance.

Accurate measurement and determination of the electromagnetic characteristics of the switched reluctance motor (SRM) are indispensable to their advanced control and performance analysis. This paper proposes a novel method for modeling the flux-linkage characteristics of SRM. This strategy without rotor locking, includes three steps, namely measuring, estimating and calculating steps. In the first step, flux linkage curves with current at four equilibrium positions are obtained by an indirect measurement method. In the second step, the flux-linkage characteristic of SRM in the middle position is estimated by its two adjacent flux-linkage curves. In the third step, a decoupled analytical model based on the five-order Fourier series is developed to construct the entire flux-linkage characteristics. The proposed method can not only eliminate the requirements on rotor clamping devices or position sensors, but also achieve fast and accurate modeling for the electromagnetic characteristics of SRM. Comparative studies are carried out between the proposed method and the conventional rotor clamping method, and the results demonstrate that the proposed method has a good agreement with the conventional rotor clamping method. Moreover, the simulation model is established in MATLAB/Simulink software based on the entire electromagnetic characteristics calculated by the proposed method. The accuracy of the proposed method is further verified by comparing the simulation and experimental results under different operating modes of the SRM.

In order to solve the problems of severe coupling, nonlinearity and speed ripple of the switched reluctance motor (SRM) drive, a combined strategy of self-tuning fuzzy PID (STFPID) control and direct torque control (DTC) is developed. The STFPID controller is used to control the motor speed in the outer loop and the DTC method is applied to the inner loop. The fuzzy logic tuning rules are obtained from the experience of operator and knowledge of specialist. The STFPID parameters are automatically adjusted on online according to the error and its change of rate of speed in the transient period. Comparative studies are carried out between the proposed STFPID controller and the classic PID controller, the results show that the STFPID controller has a good performance. The SRM drive system based on STFPID control, response speed improved by 50%, regulation accuracy and robustness are improved obviously.