Nonlinear H-infinity control for switched reluctance machines

Abstract

The article proposes a nonlinear H-infinity control method for switched reluctance machines. The dynamic model of the switched reluctance machine undergoes approximate linearization round local operating points which are redefined at each iteration of the control algorithm. These temporary equilibria consist of the last value of the reluctance machine’s state vector and of the last value of the control signal that was exerted on it. For the approximate linearization of the reluctance machine’s dynamics, Taylor series expansion is performed through the computation of the associated Jacobian matrices. The modelling errors are compensated by the robustness of the control algorithm. Next, for the linearized equivalent model of the reluctance machine an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each time-step of the control method. It is shown that the control scheme achieves H-infinity tracking performance, which implies maximum robustness to modelling errors and external perturbations. The stability of the control loop is proven through Lyapunov analysis.

Recent Trends in Minimization of Torque Ripples in Switched Reluctance Machine

“…In [55] Two types of uncertainty like variation outer disorder and the model error are in traditional H-infinity control which has an external control method. The H-infinity control mechanism is a closed loop controller, decisive the ideal control weight is difficult.…”

A Review of Fixed Switching Frequency Current Control Techniques for Switched Reluctance Machines

“…Moreover, sufficient care should be taken for application in the sampled data systems with signification sampling delays. In switched reluctance machines, the H 2 /H ∞ control techniques have found application for speed control [52], [53] and specifically for current control, [54], [55].…”

Speed Control of Switched Reluctance Motor using Adaptive Fuzzy Backstepping Sliding Mode Control

“…The research group led by Rigatos was the first to publish a comprehensive mathematical model that incorporates both the motor and the switch (inverter) [25]. However, their approach treated the SRM as a combined linear model for control algorithm design.…”

“…In particular, when changing the setpoint value, the overshoot can reach up to 50%. Building on this research [25], we retained the combined model of SRMs and applied an adaptive Backstepping sliding mode control algorithm to enhance the performance of the SRM drive system.…”