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A new approach for robust Hinfty filtering for a class of Lipschitz nonlinearsystems with time-varying uncertainties both in the linear and nonlinear partsof the system is proposed in an LMI framework. The admissible Lipschitzconstant of the system and the disturbance attenuation level are maximizedsimultaneously through convex multiobjective optimization. The resulting Hinftyfilter guarantees asymptotic stability of the estimation error dynamics withexponential convergence and is robust against nonlinear additive uncertaintyand time-varying parametric uncertainties. Explicit bounds on the nonlinearuncertainty are derived based on norm-wise and element-wise robustnessanalysis.

Robust Nonlinear L2 Filtering of Uncertain Lipschitz Systems via Pareto Optimization