Robust fault tolerant tracking controller design for unknown inputs T–S models with unmeasurable premise variables

Abstract

This work concerns the tracking problem of uncertain Takagi–Sugeno fuzzy continuous systems with unmeasurable premise variables and affected by unknown inputs. The aim is to synthesize a fault tolerant controller (FTC) ensuring trajectory tracking of a desired reference model. To emit the original plant system, a norm bounded parametric uncertainty is employed in building the T–S model. The control scheme is based on a fuzzy observer to estimate both faults and faulty system states; a proportional integer (PI) observer to estimate constant faults is then adopted. Using descriptor redundancy property and L2 optimization to attenuate the unknown inputs effect, a solution is proposed in terms of bilinear matrix inequalities (BMIs). The performances of the proposed approach are pointed out by accentuating on a model of wastewater treatment plant (WWTP) through numerical results.