<p>This study introduces a fault estimation (FE) and fault-tolerant control (FTC) scheme for discrete-time Takagi–Sugeno (T–S) fuzzy systems, addressing actuator faults, external disturbances, and uncertain systems in a nonlinear quarter-vehicle suspension model. The original nonlinear dynamics are approximated using the T–S fuzzy modeling framework, which allows the system to be represented as a convex combination of linear sub-models, creating more structured opportunities for tractable controller and observer design. In this work, an <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(H_\infty \)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>H</mi> <mi>∞</mi> </msub> </math></EquationSource> </InlineEquation> fuzzy observer is developed to permit robust state estimation and FE using Lyapunov-Krasovskii functionals (LKF) that have been recast as linear matrix inequalities (LMIs). A fuzzy linear quadratic regulator (LQR) is designed for FTC, and both the observer gain and the controller gains are optimized for improved performance using particle swarm optimization (PSO). Simulation results on a quarter-vehicle active suspension system demonstrate that the proposed method significantly improves stability, robustness, and fault-tolerance under varying system conditions.</p>