Modeling and stability analysis of HIV-1 as a time delay fuzzy T–S system via LMIs

Abstract

This paper proposes a Time Delay Fuzzy Takagi-Sugeno (T-S) representation of a nonlinear dynamic model of HIV-1 as well as stability analysis of the model. Asymptotic stability of the resulting T-S fuzzy system with state-delay is investigated and partially established. The focus is mainly on the delay-dependent stability analysis based on the fuzzy weighting-dependent Lyapunov function method.

A Novel Technique to Solve the Fuzzy System of Equations

“…Based on numerical-and semi-analytical methods for solving FSLEs, we can study fuzzy bio-mathematical models. In [7], Abbasi et al solved the fuzzy mathematical model of HIV infection and in [8], Mishra and Pandey applied the fuzzy system of equations to show the fuzzy mathematical model of computer viruses. Thus, studying the mathematical methods for solving the FSLE is important in theories and applications.…”

A fuzzy C‐regression model algorithm using a new PSO algorithm

“…Other work used the fuzzy TS to solve the problem for representation of the nonlinear dynamic model of human immunodeficiency virus, stability analysis of the model, output feedback control for the singular Markovian jump system with considering the influence of actuator saturation, and partly unknown transition probabilities. 11,12 In other more recent works, the fuzzy model design has been considered as an optimization problem, where each point represents a potential fuzzy model. Because of their powerful global searching capability, evolutionary algorithms, such as genetic algorithm, 13 genetic programming, 14 evolution strategy, 15 and differential evolution, 16 have been used to construct fuzzy models.…”