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inverse system
noun
An indexed family of groups whose index set is a directed poset, together with a set of homomorphisms which are indexed by a subset of the Cartesian product of the index set with itself — which subset corresponds to the ordering relation of the directed poset — such that the domain and codomain of each homomorphism is obtained by reversing its ordered pair of indexes (e.g., f_i j : G_j \rightarrow G_i), and such that the homomorphisms compose in a way which reflects the reflexivity and transitivity of the order relation.
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Figure 2 An approximation of the inverse system using the iterative approach.
Our method includes robust inverse system (RIS) design as a special case.
The MSLP algorithm generates an inverse filter through the prediction coefficients to estimate the inverse system [12].
A simple approach is to use the inverse system of G which is noted as G−1.
In order to obtain the de-mixing (inverse) system adaptively, a strong correlation should exist over multiple blocks.
The neural network inverse system is composed of a static neural network with several integrators and state feedback of the original chassis system to approach the inverse system of the nonlinear systems.
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By developing an approach that is valid for arbitrary coupling strength and is perturbative in the inverse system-size 1 / N, here we prove that the Floquet spectrum scales as 1 / N 2 and is proportional to F ( 1 ) − F ( 0 ).
A notion of inverse systems is crucial for linear estimation of both Wiener and Hammerstein systems, with in verses of the nonlinear or linear parts respectively involved.
This paper considers gain-scheduled approximate inverse systems for Linear Parameter-Varying (LPV) systems, and proposes a method for their design using parameter-dependent Lyapunov functions via parametrically affine Linear Matrix Inequalities (LMIs).
In the pouring control, the flow rate model of cylindrical ladle is represented by LPV(Linear Parameter Varying) model, and FeedForward(FF) controller is then designed by using inverse systems of motor and flow rate model.
This paper addresses the design problem of full-order Gain-Scheduled (GS) open-loop systems, such as GS filters and GS inverse systems, which are independent of unmeasurable parameters for Linear Parameter-Varying (LPV) systems in which the state-space matrices are polynomially parameter dependent.
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