The objective of this research is to address fundamental challenges in the verification and analysis of reconfigurable distributed hybrid control systems. These occur frequently whenever control decisions for a continuous plant depend on the actions and state of other participants. They are not supported by verification technology today. The approach advocated here is to develop strictly compositional proof-based verification techniques to close this analytic gap in cyber-physical system design and to overcome scalability issues. This project develops techniques using symbolic invariants for differential equations to address the analytic gap between nonlinear applications and present verification techniques for linear dynamics. This project aims at transformative research changing the scope of systems that can be analyzed. The proposed research develops a compositional proof-based approach to hybrid systems verification in contrast to the dominant automata-based verification approaches. It represents a major improvement addressing the challenges of composition, reconfiguration, and nonlinearity in system models The proposed research has significant applications in the verification of safety-critical properties in next generation cyber-physical systems. This includes distributed car control, robotic swarms, and unmanned aerial vehicle cooperation schemes to full collision avoidance protocols for multiple aircraft. Analysis tools for distributed hybrid systems have a broad range of applications of varying degrees of safety-criticality, validation cost, and operative risk. Analytic techniques that find bugs or ensure correct functioning can save lives and money, and therefore are likely to have substantial economic and societal impact.