State-Feedback H∞ Control for LPV System Using T-S Fuzzy Linearization Approach

Abstract EN

This paper discusses the linear parameter varying (LPV) gain scheduling control problem based on the Takagi-Sugeno (T-S) fuzzy linearization approach.

Firstly, the affine nonlinear parameter varying (ANPV) description of a class of nonlinear dynamic processes is defined; that is, at any scheduling parameter, the corresponding system is affine nonlinear as usual.

For such a class of ANPV systems, a kind of developed T-S fuzzy modeling procedure is proposed to deal with the nonlinearity, instead of the traditional Jacobian linearization approach.

More concretely, the evaluation system for the approximation ability of the novelly developed T-S fuzzy modeling procedure is established.

Consequently, the LPV T-S fuzzy system is obtained which can approximate the ANPV system with required accuracy.

Secondly, the notion of piecewise parameter-dependent Lyapunov function is introduced, and then the stabilization problem and the state-feedback H∞ control problem of the LPV T-S fuzzy system are studied.

The sufficient conditions are given in linear matrix inequalities (LMIs) form.

Finally, a numerical example is provided to demonstrate the availability of the above approaches.

The simulation results show the high approximation accuracy of the LPV T-S fuzzy system to the ANPV system and the effectiveness of the LPV T-S fuzzy gain scheduling control.