Covariance-analytic performance criteria, Hardy-Schatten norms and Wick-like ordering of cascaded systems

TL;DR

This paper introduces covariance-analytic performance criteria for linear stochastic systems, linking higher-order Hardy-Schatten norms with system robustness and providing recursive computational methods using Wick-like ordering of cascaded systems.

Contribution

It develops a recursive method for computing Hardy-Schatten norms via a Wick-like ordering technique, connecting covariance-analytic costs with system robustness and $ ext{H}_2$ norms.

Findings

The covariance-analytic cost can be expressed as the squared $ ext{H}_2$-norm of an auxiliary system.

The recursive computation involves algebraic Lyapunov equations.

Comparison with Riccati-based approaches shows the method's effectiveness.

Abstract

This paper is concerned with linear stochastic systems whose output is a stationary Gaussian random process related by an integral operator to a standard Wiener process at the input. We consider a performance criterion which involves the trace of an analytic function of the spectral density of the output process. This class of "covariance-analytic" cost functionals includes the usual mean square and risk-sensitive criteria as particular cases. Due to the presence of the "cost-shaping" analytic function, the performance criterion is related to higher-order Hardy-Schatten norms of the system transfer function. These norms have links with the asymptotic properties of cumulants of finite-horizon quadratic functionals of the system output and satisfy variational inequalities pertaining to system robustness to statistically uncertain inputs. In the case of strictly proper finite-dimensional systems, governed in state space by linear stochastic differential equations, we develop a method for recursively computing the Hardy-Schatten norms through a recently proposed technique of rearranging cascaded linear systems, which resembles the Wick ordering of annihilation and creation operators in quantum mechanics. The resulting computational procedure involves a recurrence sequence of solutions to algebraic Lyapunov equations and represents the covariance-analytic cost as the squared $\mathcal{H}_2$-norm of an auxiliary cascaded system. These results are also compared with an alternative approach which uses higher-order derivatives of stabilising solutions of parameter-dependent algebraic Riccati equations.