Fuzzy nonlinear adaptive internal model control (FNAIMC) part I: Fuzzy model identification

This two part paper proposes an adaptive fuzzy internal model control of nonlinear systems which uses a Takagi-Sugeno fuzzy model of the process. The main objective of this first part is to identify the fuzzy model of the plant. The identification task is decomposed into structure identification (number of rules) and parameter identification (singleton consequences of the rules). The stability and convergence of the proposed method is guaranteed via Lyapunov synthesis.