Multiplier-based Observer Design for Large-Scale Lipschitz Systems

Observer design for nonlinear systems with incomplete state observations is of practical significance. Despite numerous existing works and recent developments in handling multiple types of nonlinearities, it is still an open challenge to reduce conservatism of synthesis conditions for systems with large Lipschitz constants, and to improve computational efficiency for complex real-world dynamics. To this end, this study presents a multiplier-based approach that is capable of determining an asymptotically stable observer for a large class of highly nonlinear and large-scale systems. These key advantages are due to an informative quadratic constraint on the nonlinear dynamics. Both the present and the state-of-theart methods are evaluated in a benchmark example and a case study on the dynamic power system state estimation, where the proposed approach exhibits an imperative trade-off between non-conservatism and computational tractability, establishing its viability for real-world large-scale nonlinear systems.