Decentralized Sampled-Data Tracking Control of Large-Scale Fuzzy Systems: An Exact Discretization Approach

In this paper, a decentralized sampled-data tracking controller design technique for Takagi-Sugeno fuzzy interconnected systems is proposed. The overall large-scale system is assumed to consist of fuzzy subsystems with unknown but norm-bounded interconnections. This paper focuses mainly on the design of a sampled-data decentralized model reference tracking controller based on the exact discretization approach, by which the resulting large-scale error dynamics becomes asymptotically stabilized with a predefined H-infinity performance criterion. To this end, we first design a continuous-time decentralized tracking controller based on the proposed design technique. After that, by using the discrete-time fuzzy Lyapunov function, the proposed design technique is extended to cover a sampled-data tracking controller design. The proposed controller design techniques are formulated in terms of linear matrix inequalities. Finally, numerical examples are given to show the effectiveness of the proposed methods by comparing them with other methods.