Design of optimal reduced order filter for unstable discrete time systems

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Design of optimal reduced order filter for unstable discrete time systems

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The paper is concerned with H2 optimal reduced-order filtering for a linear discrete time signal model. The signal model is allowed to be unstable. The objective is to obtain a reduced-order filter that not only gives rise to a stable filtering error transfer function but also minimises the H2 norm. The authors first derive a parameterisation of a set of filters of fixed order which lead to stable filtering error transfer functions. Such a parameterisation is given in terms of an arbitrary orthogonal projection matrix. As a consequence, the problem of minimising the H2 norm of the filtering error transfer function over the set of reduced-order filters is formulated as an equivalent unconstrained parametric optimisation problem over a compact manifold. Two gradient-based algorithms are then proposed to compute an optimal reduced-order filter. The good properties of the algorithms, including the convergence property, are established theoretically as well as demonstrated numerically with an example.

Inspec keywords: filtering theory; linear systems; convergence; transfer functions; discrete time systems; optimisation; reduced order systems

Other keywords: gradient-based algorithms; optimal reduced order filter; H2 optimal reduced-order filtering; compact manifold; linear discrete time signal model; parameterisation; stable filtering error transfer function; unstable discrete time systems; unconstrained parametric optimisation problem; convergence property

Subjects: Optimisation techniques; Discrete control systems; Simulation, modelling and identification; Filtering methods in signal processing; Signal processing theory; Optimisation techniques; Control system analysis and synthesis methods

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