Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy controller with stability and performance rules for nonlinear systems
Fuzzy Sets and Systems
Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems
Information Sciences: an International Journal
Relaxed conditions in tracking control design for a TS fuzzy model
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Adaptive fuzzy output tracking control for a class of uncertain nonlinear systems
Fuzzy Sets and Systems
Perspectives of fuzzy systems and control
Fuzzy Sets and Systems
An adaptive fuzzy system for the control of the vergence angle on a robotic head
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
A control strategy for platoons of differential drive wheeled mobile robot
Robotics and Autonomous Systems
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
Observer synthesis for the T-S fuzzy system with uncertainty and output disturbance
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
MIMO fuzzy identification of building-MR damper systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Information Sciences: an International Journal
Iterative performance improvement of fuzzy control systems for three tank systems
Expert Systems with Applications: An International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On the stability issues of linear Takagi-Sugeno fuzzy models
IEEE Transactions on Fuzzy Systems
Interpolation with function space representation of membership functions
IEEE Transactions on Fuzzy Systems
MIN and MAX Operators for Fuzzy Intervals and Their Potential Use in Aggregation Operators
IEEE Transactions on Fuzzy Systems
Piecewise Integral Sliding-Mode Control for T–S Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
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This paper presents a new stability analysis method dedicated to a class of fuzzy control systems FCSs controlling multi input-multi output MIMO nonlinear processes by means of Takagi-Sugeno-Kang fuzzy logic controllers FLCs. The stability analysis of the FCSs is carried out using LaSalle's global invariant set theorem by the separate stability analysis of each fuzzy rule in MIMO fuzzy control systems. Therefore the complexity of the stability analysis is reduced and the adding of new fuzzy rules can be conducted easily; this modification of FLC structure requires the fulfillment of only one of the conditions of the stability analysis theorem suggested in this paper. Another advantage of the stability analysis approach proposed in this paper is that the derivative of the Lyapunov function candidate must be only negative semi-definite in comparison with Lyapunov's stability theorem where it must be negative definite. The conservativeness of stability conditions is thus reduced, and this enables the convenient design of FLCs. The applicability and efficiency of the theoretical results are illustrated by numerical simulations for a representative MIMO process which deals with the level control in a three spherical tank system.