Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Analysis and design for a class of complex control systems part II: fuzzy controller design
Automatica (Journal of IFAC)
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
Piecewise quadratic stability of fuzzy systems
IEEE Transactions on Fuzzy Systems
Robust fuzzy control of nonlinear systems with parametric uncertainties
IEEE Transactions on Fuzzy Systems
Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model
IEEE Transactions on Fuzzy Systems
An approach to adaptive control of fuzzy dynamic systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A multiple Lyapunov function approach to stabilization of fuzzy control systems
IEEE Transactions on Fuzzy Systems
Synchronization of chaotic systems from a fuzzy regulation approach
Fuzzy Sets and Systems
Stabilizing fuzzy output control for a class of nonlinear systems
Advances in Fuzzy Systems - Special issue on Fuzzy Logic Applications in Control Theory and Systems Biology
Stabilizing fuzzy output control for a class of nonlinear systems
Advances in Fuzzy Systems - Special issue on Fuzzy Logic Applications in Control Theory and Systems Biology
Relaxed stability issues for T-S fuzzy system: Based on a fuzzy quadratic Lyapunov function
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In this paper, new non-quadratic stability conditions are derived based on the parallel distributed compensation scheme to stabilize Takagi-Sugeno (T-S) fuzzy systems. We use a non-quadratic Lyapunov function as a fuzzy mixture of multiple quadratic Lyapunov functions. The quadratic Lyapunov functions share the same membership functions with the T-S fuzzy model. The stability conditions we propose are less conservative and stabilize also fuzzy systems which do not admit a quadratic stabilization. The proposed approach is based on two assumptions. The first one relates to a proportional relation between multiple Lyapunov functions and the second one considers an upper bound to the time derivative of the premise membership functions. To illustrate the advantages of our proposal, four examples are given.