In this paper, the problem of designing a controller for a highly coupled constrained nonlinear boilerturbine system is addressed with a predictive controller. First, a nonlinear predictive control is implemented by genetic algorithm. Second, to guarantee fast output stabilization, an H-infinity fuzzy state-feedback tracking control is applied with a designed switching principle. The success of such a control structure is based on taking advantage of the optimal input sequence derived from the nonlinear predictive control based on artificial intelligent while ensuring a fast decay of the steady state error. Simulation results of the proposed design are given to illustrate its effectiveness and compared to other control schemes.
Jie WUJiong SHENMattias KRUGSing Kiong NGUANGYiguo LI
Solid oxide fuel cells (SOFCs) are considered to be one of the most important clean,distributed resources. However,SOFCs present a challenging control problem owing to their slow dynamics,nonlinearity and tight operating constraints. A novel data-driven nonlinear control strategy was proposed to solve the SOFC control problem by combining a virtual reference feedback tuning (VRFT) method and support vector machine. In order to fulfill the requirement for fuel utilization and control constraints,a dynamic constraints unit and an anti-windup scheme were adopted. In addition,a feedforward loop was designed to deal with the current disturbance. Detailed simulations demonstrate that the fast response of fuel flow for the current demand disturbance and zero steady error of the output voltage are both achieved. Meanwhile,fuel utilization is kept almost within the safe region.
