Fuzzy Supervisory Passivity-Based High Order-Sliding Mode Control Approach for Tidal Turbine-Based Permanent Magnet Synchronous Generator Conversion System

Abstract

Higher efficiency, predictability, and high-power density are the main advantages of a permanent magnet synchronous generator (PMSG)-based hydro turbine. However, the control of a PMSG is a nontrivial issue, because of its time-varying parameters and nonlinear dynamics. This paper suggests a novel optimal fuzzy supervisor passivity-based high order sliding-mode controller to address problems faced by conventional techniques such as PI controls in the machine side. An inherent advantage of the proposed method is that the nonlinear terms are not canceled but compensated in a damped way. The proposed controller consists of two main parts: the fuzzy gain supervisor-PI controller to design the desired dynamic of the system by controlling the rotor speed, and the fuzzy gain-high order sliding-mode control to compute the controller law. The main objectives are feeding the electrical grid with active power, extracting the maximum tidal power, and regulating the reactive power and DC voltage toward their references, whatever the disturbances caused by the PMSG. The main contribution and novelty of the present work consists in the new robust fuzzy supervisory passivity-based high order sliding-mode controller, which treats the mechanical characteristics of the PMSG as a passive disturbance when designing the controller and compensates it. By doing so, the PMSG tracks the optimal speed, contrary to other controls which only take into account the electrical part. The combined high order sliding-mode controller (HSMC) and passivity-based control (PBC) resulted in a hybrid controller law which attempts to greatly enhance the robustness of the proposed approach regardless of various uncertainties. Moreover, the proposed controller was also validated using a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad. The control strategy was tested under parameter variations and its performances were compared to the nonlinear control methods. High robustness and high efficiency were clearly illustrated by the proposed new strategy over compared methods under parameter uncertainties using MATLAB/Simulink and a PIL testing platform.

Efficiency Maximization of Grid-Connected Tidal Stream Turbine System: A Supervisory Energy-Based Speed Control Approach with Processor in the Loop Experiment

“…The DC-link PI gains are: k dcp = 5 and k dci = 500. The investigated strategy is compared with other nonlinear controls to show its superiority, with the fuzzy passivity-based linear feedback current control (FPBLFC) proposed in [17], the passivity-based current control (PBCC) proposed in [18], the high-order sliding mode control (HSMC) [7], and the passivity-based fuzzy high order sliding mode (PBC-HSMC) [31]. The proposed method is tested under two scenarios.…”

Lateral Stability Control of Four-Wheel-Drive Electric Vehicle Based on Coordinated Control of Torque Distribution and ESP Differential Braking

“…The fuzzy control system can handle the uncertain relationship of various complex systems [40], so in order to track the expected state of electric vehicle, a fuzzy controller was designed. The difference between the expected and actual yaw velocity and centroid angle are taken as two vague input variables, and the modifier of the yaw moment is the output variable.…”

Architecture of Distributed Control System for Gearbox-Free More Electric Turbofan Engine

“…Two types of electrical machines are considered as alternatives to synchronous generators: the permanent magnet synchronous electric machine (PMSM) and the switch reluctance electric machine (SRM) [15][16][17][18]. Three phase PMSM and four phase SRM, each with its own advantages and disadvantages, are reviewed for use as engine electric machines [19][20][21][22][23][24].…”