Design of fuzzy robust control strategies for a distributed solar collector field

Abstract

This paper presents novel control strategies using Takagi–Sugeno fuzzy models combined with a parametric uncertainty robust control approach to address both the nonlinearities of a process and the disturbances that act on it. In contrast to other robust control approaches, such as the H∞ norm optimization-based approach, the proposed techniques allow the uncertainty information provided by fuzzy confidence intervals to be used to derive controllers that take into account performance specifications, such as overshoot or disturbance rejection, and to ensure the robust stability of the system due to a study based on applying the generalized Kharitonov's theorem and Lyapunov's analysis from the solution of a linear matrix inequality (LMI). To test these novel strategies, a solar collector field, which is a nonlinear plant with several disturbances affecting its operation, is used. For this plant, fuzzy confidence intervals are derived that allow representing the uncertainties associated with these disturbances, different performance objectives are tested, and a methodology for deriving these controllers is developed. The effectiveness of this approach is demonstrated on the solar collector field under different solar radiation conditions, and promising results are obtained.