Data-driven Nonlinear Control of a Solid Oxide Fuel Cell System

Abstract

AbstractSolid oxide fuel cells (SOFCs) are considered to be one of the most important clean, distributed resources. However, they present a challenging control problem owing to the SOFC's slow dynamics, nonlinearity and tight operating constraints. In this paper, we propose a novel data-driven nonlinear control strategy to solve the SOFC control problem by combining a virtual reference feedback tuning (VRFT) method with support vector machine (SVM). In order to fulfill the requirement for fuel utilization and control constraints, a dynamic constraints unit plus an anti-windup scheme are adopted. In addition, a feedforward loop is designed to deal with the current disturbance. Detailed simulations are given to demonstrate the feasibility of control application to fuel cell plants.