Stability of cascaded fuzzy systems and observers

Zs. Lendek, R. Babuska, and B. De Schutter, "Stability of cascaded fuzzy systems and observers," IEEE Transactions on Fuzzy Systems, vol. 17, no. 3, pp. 641-653, June 2009.

A large class of nonlinear systems can be well approximated by Takagi-Sugeno (TS) fuzzy models, with linear or affine consequents. It is well-known that the stability of these consequent models does not ensure the stability of the overall fuzzy system. Therefore, several stability conditions have been developed for TS fuzzy systems. We study a special class of nonlinear dynamic systems that can be decomposed into cascaded subsystems, represented as TS fuzzy models. We analyze the stability of the overall TS system based on the stability of the subsystems, and prove that the stability of the subsystems implies the stability of the overall system. The main benefit of this approach is that it relaxes the conditions imposed when the system is globally analyzed, thereby solving some of the feasibility problems. Another benefit is that by using this approach, the dimension of the associated linear matrix inequality (LMI) problem can be reduced. For naturally distributed applications, such as multi-agent systems, the construction and tuning of a centralized observer may not be feasible. Therefore, we extend the cascaded approach also to observer design, and use fuzzy observers to individually estimate the states of these subsystems. A theoretical proof of stability and simulation examples are presented. The results show that the distributed observer achieves the same performance as the centralized one, while leading to increased modularity, reduced complexity, lower computational costs, and easier tuning. Applications of such cascaded systems include multi-agent systems, distributed process control, and hierarchical large-scale systems.

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Bibtex entry:

        author={{\relax Zs}. Lendek and R. Babu{\v{s}}ka and B. {D}e Schutter},
        title={Stability of cascaded fuzzy systems and observers},
        journal={IEEE Transactions on Fuzzy Systems},

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