Exact model matching of linear time-varying systems

1978 ◽  
Vol 125 (1) ◽  
pp. 66 ◽  
Author(s):  
P.N. Paraskevopoulos
Keyword(s):  
Linear Time ◽  
Time Varying ◽  
Model Matching ◽  
Exact Model ◽  
Time Varying Systems

Uniform exact model matching for a class of linear time-varying analytic systems

1992 ◽  
Vol 19 (4) ◽  
pp. 313-323 ◽  
Author(s):  
K.G. Arvanitis ◽  
P.N. Paraskevopoulos
Keyword(s):  
Linear Time ◽  
Time Varying ◽  
Model Matching ◽  
Exact Model

scholarly journals Adaptive Data-Driven Control for Linear Time Varying Systems

Machines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 167
Author(s):  
Talal Abdalla
Keyword(s):  
Design Problem ◽  
Controller Design ◽  
Reference Model ◽  
Linear Time ◽  
Convex Relaxation ◽  
Data Driven ◽  
Time Varying ◽  
Model Matching ◽  
Control Approach ◽  
Time Varying Systems

In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First, using set-membership identification techniques, we formulate the controller design problem through a model-matching scheme, i.e., designing a controller such that the closed-loop behaviour matches that of a given reference model. The problem is then reformulated as to derive a controller that corresponds to the minimum variation bounding its parameters. Finally, a convex relaxation approach is proposed to solve the formulated controller design problem by means of linear programming. The effectiveness of the proposed scheme is demonstrated by means of two simulation examples.

scholarly journals The VIT Transform Approach to Discrete-Time Signals and Linear Time-Varying Systems

Eng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 99-125
Author(s):  
Edward W. Kamen
Keyword(s):  
Discrete Time ◽  
Initial Conditions ◽  
Linear Time ◽  
Order Term ◽  
Initial Time ◽  
Time Varying ◽  
Varying Coefficients ◽  
Time Signals ◽  
Time Varying Systems ◽  
Time Varying Coefficients

A transform approach based on a variable initial time (VIT) formulation is developed for discrete-time signals and linear time-varying discrete-time systems or digital filters. The VIT transform is a formal power series in z−1, which converts functions given by linear time-varying difference equations into left polynomial fractions with variable coefficients, and with initial conditions incorporated into the framework. It is shown that the transform satisfies a number of properties that are analogous to those of the ordinary z-transform, and that it is possible to do scaling of z−i by time functions, which results in left-fraction forms for the transform of a large class of functions including sinusoids with general time-varying amplitudes and frequencies. Using the extended right Euclidean algorithm in a skew polynomial ring with time-varying coefficients, it is shown that a sum of left polynomial fractions can be written as a single fraction, which results in linear time-varying recursions for the inverse transform of the combined fraction. The extraction of a first-order term from a given polynomial fraction is carried out in terms of the evaluation of zi at time functions. In the application to linear time-varying systems, it is proved that the VIT transform of the system output is equal to the product of the VIT transform of the input and the VIT transform of the unit-pulse response function. For systems given by a time-varying moving average or an autoregressive model, the transform framework is used to determine the steady-state output response resulting from various signal inputs such as the step and cosine functions.

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