Reduced-Order Nonlinear Observers Via Contraction Analysis and Convex Optimization

In this article, we propose a new approach to design globally convergent reduced-order observers for nonlinear control systems via contraction analysis and convex optimization. Despite the fact that is concept naturally suitable state estimation, existing solutions are either local or relatively conservative when applying physical systems. To address this, show problem can be translated into an offline search coordinate transformation after which dynamics (transversely) contracting. The obtained sufficient condition consists of some easily verifiable differential inequalities, which, on one hand, identify very general class “detectable” systems, other expressed as computationally efficient optimization, making procedure more systematic. Connections with well-established approaches concepts also clarified in article. Finally, illustrate proposed method several numerical examples, including polynomial, mechanical, electromechanical, biochemical