A memory control for T-S fuzzy discrete-time systems with sto- chastic input delay is proposed in this paper. Dierent from the common assumptions on the time delay in the existing literatures, it is assumed in this paper that the delays vary randomly and satisfy some probabilistic dis- tribution. A new state space model of the discrete-time T-S fuzzy system is derived by introducing some stocha...

A simple easy to implement algorithm is proposed to address wall tracking task of an autonomous robot. The robot should navigate in unknown environments, find the nearest wall, and track it solely based on locally sensed data. The proposed method benefits from coupling fuzzy logic and Q-learning to meet requirements of autonomous navigations. Fuzzy if-then rules provide a reliable decision maki...

This paper is concerned with the input-output-to-state stability for switched fuzzy neural networks. A new set of matrix norm based conditions is proposed such that switched fuzzy neural networks are input-output-to-state stable. A modified set of conditions for asymptotic stability of switched fuzzy neural networks is also presented in this paper. Keywords— input-output-to-state stability, swi...

In multi-view modeling languages like UML, models contain several diagrams, each of which focusing on a specific aspect of the system. However, when the diagrams are combined, they give a coherent description of all static and dynamic aspects of the system. Diagrams may then extend each other or add constraints to other diagrams. Considering this additional information improves model versioning...

This paper introduces Fuzzy State Automata for control applications. They are derived from the integration of traditional nite state automata and neuro-fuzzy systems, where a nite state automaton tracks the state of the plant under control and modiies the characteristic of the neuro-fuzzy system accordingly. The main diierence with respect to existing systems is that the states of the automata ...