title: Relaxed stability and performance conditions for Takagi-Sugeno fuzzy systems with knowledge on membership function overlap.
abstract: This correspondence presents a relaxation of some earlier linear matrix inequality (LMI) conditions, which allow setting up less conservative stability or performance conditions for Takagi-Sugeno fuzzy models. Unlike the previous literature, this correspondence takes into account the knowledge of the membership functions' shape by considering bounds on them and their cross products (interpreted as an overlap measure), introducing auxiliary LMI variables. Numerical examples illustrate the achieved improvements.
authors.forename: Antonio
authors.initials: A
authors.lastname: Sala
authors.forename: Carlos
authors.initials: C
authors.lastname: Ariño
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008390:Markov Chains; D015233:Models, Statistical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D013269:Stochastic Processes