Affine TS-model-based fuzzy regulating/servo control design

An affine T-S fuzzy system is derived naturally from linearizing a nonlinear system or from some data-driven identification techniques, for example, cluster-based algorithms or soft-computation learning structures. Little research is proposed for the intrinsic analysis of an affine-type fuzzy system. Further, the controllers to regulate or to achieve servo control of affine TS-based nonlinear systems are also few. Both affine-type fuzzy regulation and servo control design scheme are theoretically derived. A simple Lyapunov-based stability criterion and some extra conditions are proposed to guarantee the global stability of the generated closed-loop fuzzy systems. The exponential stability of the feedback fuzzy system is ensured under some conditions. The performance of the proposed fuzzy controllers and fuzzy servo controllers is examined by three case studies. Simulation results show that the proposed controllers can stabilize these affine fuzzy systems and the proposed servomechanism can adapt itself to various incoming signals in very short time spans.