 A new control design could help engineers improve the stability of long, slender beams, including those used for offshore drilling. Numerous important dynamical systems are governed by non-linear partial differential equations, from chemical reactions to epidemics to engineering structures. While optimal control designs have been established for these highly complex systems, doing so is extremely difficult. The inverse control approach has proven useful for extending optimal designs from linear to non-linear systems, but for the most part, only for Euclidean spaces. Extension to Hilbert spaces faces the formidable obstacle of having to solve a Hamilton-Jakobi-Bellman equation. Now, researchers have found a way to surmount that barrier, formulating a control design that can be used to reliably stabilize extensible and shearable beams. The team first formulated an optimal stabilization problem through an inverse approach and solved for non-linear evolution systems in Hilbert spaces. The optimal control design possesses two highly attractive features. First, it ensures both global well-posedness and global practical K-infinity exponential stability of the closed-loop system. And second, it minimizes a cost functional that appropriately penalizes both state and control, such that it is positive definite in the state and control, all without having to solve a Hamilton-Jakobi-Bellman equation. The Lyapunov functional used in the control design explicitly solves a family of such equations. The team applied the results to design inverse optimal boundary stabilization control laws for extensible and shearable slender beams governed by fully non-linear partial differential equations. Researchers like these are found in numerous applications in offshore and structural engineering. The resulting control laws are optimal in the sense that both the motion of the beams and the boundary controls are minimized, thereby improving current beam control systems. More work is needed to meet the more rigorous standard of asymptotic rather than simply exponential stability. And of course, tests in real-world settings are in order. These early findings might already be remarkably useful, as the new control design overcomes a long-standing barrier to achieving stability in many pervasive complex systems.