Global stabilization of nonlinear cascade systems
Systems & Control Letters
A Unifying Integral ISS Framework for Stability of Nonlinear Cascades
SIAM Journal on Control and Optimization
Distributed particle filters for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Relaxed stability and stabilization conditions for a T--S fuzzy discrete system
Fuzzy Sets and Systems
Resampling algorithms and architectures for distributed particle filters
IEEE Transactions on Signal Processing
Observers for Takagi-Sugeno fuzzy systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs
IEEE Transactions on Fuzzy Systems
Piecewise quadratic stability of fuzzy systems
IEEE Transactions on Fuzzy Systems
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
Sequential stability analysis and observer design for distributed TS fuzzy systems
Fuzzy Sets and Systems
Rule base identification in fuzzy networks by Boolean matrix equations
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Alarge 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, which are 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 multiagent systems, the construction and tuning of a centralized observer may not be feasible. Therefore, we also extend the cascaded approach to the 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 multiagent systems, distributed process control, and hierarchical large-scale systems.