Sensorless fuzzy sliding mode control for permanent magnet synchronous motor fed by AC/DC/AC converter

Abstract

In this paper a systematic fuzzy sliding mode controller is presented for permanent magnet synchronous motor (PMSM) sensorless drives. The fuzzy sliding mode controller is designed based on input-output feedback linearization control technique. The extended Kalman filter is used to estimate the speed, position and load torque. The PMSM is fed from indirect power electronics converter. This indirect converter is controlled by the sliding mode technique. This control technique allows the minimization of harmonics introduced by the line converter, including the control of power factor and DC-link voltage. The robustness of the overall system is studied using simulation for different operating modes and varied parameters.

Comparative Study between Sliding Mode Control and the Vectorial Control of a Brushless doubly fed induction generator

“…In fact, the Lyapunov like stability condition guarantees that the distance between the system state and the surface decreases along all system trajectories and constrains the trajectories to move toward the sliding surface [21]. The advantages of the sliding mode controller can be summarized as follows [22]:  Fast response with no overshoot.  No steady state error.…”

“…Intuitively, the existence of a sliding mode on the sliding surface implies stability of the system. One of the possible solutions is given by: 22) in to (17), obtain:…”

Reduction of periodic speed ripples in switched reluctance motor using fuzzy logic control

“…FUZZY LOGIC CONTROLLER Fuzzy control systems are rule-based systems in which a set of so-called fuzzy rules represent a control decision mechanism to adjust the effects of certain system stimulus. The aim of fuzzy control systems is normally to replace a skilled human operator with a fuzzy rule-based system [14,15].…”

“…The control rules are designed to assign a fuzzy set of the control input u for each combination of fuzzy sets of (e) and e [15,16,17,18]. Table 1 shows rule base of the fuzzy logic controller.…”