Computing and Optimizing the $H^2$-norm of Delay Differential Algebraic Systems
We present a Lanczos tau method for the approximation and optimization of the $H^2$-norm of time-delay systems described by semi-explicit delay differential algebraic equations. The soundness of this approach is proven under the assumption of a finite strong $H^2$-norm. Furthermore, we prove convergence if the rational approximation of the exponential underlying the discretization is well-behaved and the discretization is stability preserving. Numerical results suggest that, for multiple delays, the method converges at cubic rate in the discretization degree for systems of retarded type and linearly for those of neutral type. In the single delay case, we note geometric convergence of the $H^2$-norm for systems of both retarded and neutral type when a symmetric basis is chosen. Explicit formulas are derived for the gradient of the approximation with respect to system parameters and delays. These allow us to compute the entire gradient using only about double the computational time of approximating the $H^2$-norm alone. We illustrate how these can be used to synthesize robust feedback controllers and stable approximate models. The article is concluded by a discussion of how the presented results extend and improve for approximations based on splines. We note acceleration of the convergence rate by about two orders for such a choice. Finally, we prove that a Lanczos tau method using a spline based on Legendre orthogonal polynomials preserves stability and guarantees convergence of the $H^2$-norm.