  A new approach for robust Hinfty filtering for a class of Lipschitz nonlinear
systems with time-varying uncertainties both in the linear and nonlinear parts
of the system is proposed in an LMI framework. The admissible Lipschitz
constant of the system and the disturbance attenuation level are maximized
simultaneously through convex multiobjective optimization. The resulting Hinfty
filter guarantees asymptotic stability of the estimation error dynamics with
exponential convergence and is robust against nonlinear additive uncertainty
and time-varying parametric uncertainties. Explicit bounds on the nonlinear
uncertainty are derived based on norm-wise and element-wise robustness
analysis.
