Stabilizing Fuzzy Output Control for a Class of Nonlinear Systems

Abstract

The paper presents new conditions suitable in design of a stabilizing output controller for a class of continuous-time nonlinear systems, represented by Takagi-Sugeno models. Taking into account the affine properties of the TS model structure and applying the fuzzy control scheme relating to the parallel distributed output compensators, the sufficient design conditions are outlined in terms of linear matrix inequalities. The proposed procedure decouples the Lyapunov matrix and the system parameter matrices in the LMIs and guarantees global stability of the system. Simulation result illustrates the design procedure and demonstrates the performances of the proposed design method.

Relaxed formulation of the design conditions for Takagi-Sugeno fuzzy virtual actuators

“…Using the same set of membership functions, the fuzzy static output controller in the parallel distributed form is defined as [8] …”

Output PI control of MIMO linear continuous-time systems

“…[15], [16] and [3], [8], respectively, and the reference therein. Because of the importance of those control systems, considerable attention was dedicated to the study of suitable design methods.…”

Performance evaluation of conventional and intelligent controller based shunt active filter

“…Fuzzy logic controllers (FLCs) [14,15] are intelligent control systems characterized by a set of linguistic statements based on expert knowledge or experience. Fuzzy logic was first proposed by Lotfi A. Zadeh of the University of California.…”

“…In the case of a PI type FLC, the actual value of the controller output is obtained by Eq. (10) as follows: (14) where u(k) is the controller output, u(k-1) the (k-1) th instant controller output and Δu(k) the incremental change in controller output , which is determined by the rules of the form If e is E and e is E, then u is In this method, input voltage Vdc and the input reference voltage Vdcref have been placed of the angular velocity to be the input variables of the fuzzy logic controller. Then the output variable of the fuzzy logic controller is presented by the control Current Imax.…”