H2 / H∞ FIR Filters for Discrete-time State Space Models
نویسندگان
چکیده
In this paper a new type of filter, called the H2 / H∞ FIR filter, is proposed for discretetime state space signal models. The proposed filter requires linearity, unbiased property, FIR structure, and independence of the initial state information in addition to the performance criteria in both H2 and H∞ sense. It is shown that H2, H∞, and H2 / H∞ FIR filter design problems can be converted into convex programming problems via linear matrix inequalities (LMIs) with a linear equality constraint. Simulation studies illustrate that the proposed FIR filter is more robust against temporary uncertainties and has faster convergence than the conventional IIR filters.
منابع مشابه
On Nonlinear Filters for Mixed H 2 / H " Estimation *
We study the problem of mixed least-meansquares/H"-optimal (or mixed H2/Hm-optimal) estimation of signals generated by discrete-time, finitedimensional, linear state-space models. The major result is that, for finite-horizon problems, and when the stochastic disturbances have Gaussian distributions, the optimal solutions have finite-dimensional (i.e. , bounded-order) nonlinear state-space struc...
متن کاملRisk Sensitive Fir Filters for Stochastic Discrete-time State Space Models
In this paper, the finite impulse response (FIR) filter based on an exponential quadratic cost function is proposed for a stochastic discrete-time state space model. The joint probability density function of the current state and the external noises on the recent finite horizon is introduced and the corresponding expected value of the exponential quadratic cost function is minimized with respec...
متن کاملMixed H2/H∞ optimal signal reconstruction in noisy filter banks
We study the design of synthesis filters in noisy filter bank systems using an H” estimation point of view. The H m approach is most promising in situations where the statistical properties of the disturbances (arising from quantization, compression, etc.) in each subband of the filter bank is unknown, or is too difficult to model and analyze. For arbitrary analysis polyphase matrices, standard...
متن کاملInfinite-impulse and Finite-impulse Response Filters for Continuous-time Parameter Estimation
This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse response (FIR) filters. The IIR filters use continuous time state variable filters, and discretisation is performed on the filtered derivatives. In contrast, the FIR filters are in ...
متن کاملDiscrete-Time State Estimation Using Unbiased FIR Filters with Minimized Variance
Optimal or unbiased estimators are widely used for state estimation and tracking. We propose a new minimum variance unbiased (MVU) finite impulse response (FIR) filter which minimizes the estimation error variance in the unbiased FIR (UFIR) filter. The relationship between the filter gains of the MVU FIR, UFIR and optimal FIR (OFIR) filters is found analytically. Simulations provided using a po...
متن کامل