Performance Analysis of Conjugate Gradient Algorithms Applied to the Neuro-Fuzzy Feedback Linearization-Based Adaptive Control Paradigm for Multiple HVDC Links in AC/DC Power System
This paper describes a Direct Torque Controlled (DTC) Induction Machine (IM) drive that employs feedback linearization and sliding-mode control. A feedback linearization approach is investigated, which yields a decoupled linear IM model with two state variables: torque and stator flux magnitude. This intuitive linear model is used to implement a DTC type controller that preserves all DTC advantages and eliminates its main drawback, the flux and torque ripple. Robust, fast, and ripple-free control is achieved by using Variable Structure Control (VSC) with proportional control in the vicinity of the sliding surface. The VSC component assures robustness as in DTC, while the proportional component eliminates the torque and flux ripple. The torque time response is similar to DTC and the proposed solution is flexible and highly tunable due to the proportional controller. The controller design and its robust stability analysis are presented. The sliding controller is compared with a linear DTC scheme, and experimental results for a sensorless IM drive validate the proposed solution.