Beyond the Eigenvalue (and even Linear Algebra):

The Problem Statement

For nearly seven decades, the control systems community has built its foundations on linear algebra that relies heavily on eigenvalues and matrix inversions. These methods are the industry standard, taught in every engineering university and applied in standard toolboxes like MATLAB.

However, as hardware evolves, a hidden cost has emerged. In high-performance environments—such as autonomous drone swarms and advanced air mobility applications, wireless communication networks, and real-time robotics—every milliwatt of power and every millisecond of processing time counts.

The Reality: Legacy algorithms that require complex matrix inversions and eigenvalue computations impose a heavy "computational tax" on hardware. This leads to higher energy consumption, increased heat generation, and processing lag that modern systems simply cannot afford. It is time for legacy measures such as eigenvalues and singular values to give way to more machine amenable measures such as our Toolbox's always real Convex Stability Indices (CSIs) since the legacy measures are becoming outdated.

The RES Solution & IP Validation

Robust Engineering Systems (RES) has developed a proprietary framework that moves beyond these limitations. Our RES CSSP Toolbox ensures stability and computational savings without ever needing to calculate an eigenvalue or invert a matrix.

By utilizing simple, real scalars, we have bridged the gap between theoretical Convex Stability and practical Computational Stability. We are proud to announce that this framework is backed by officially awarded intellectual property:

Patent Highlights

Key Benefits