Discrete-time Left-coprime Factors for LPV/LFR Systems

2020 ◽  
Author(s):  
Luiz Benicio Degli Esposte Rosa ◽  
Renan Lima Pereira
Keyword(s):  
Discrete Time ◽  
Special Structure ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Factorization Problem ◽  
Numerical Example ◽  
Coprime Factorization ◽  
Lpv Systems ◽  
Parameter Varying ◽  
Filtering Problem

This paper presents novel LMI-based conditions to address the discrete-time left-coprime factorization problem for linear parameter-varying (LPV) systems using linear fractional representation (LFR). The conditions have been derived using a special structure for the output injection approach, which from a given observation law allows us to synthesize left-coprime factors via the H2 filtering problem. An important characteristic of the proposed method is the ability to recover the normalized coprime factorization notion as a particular case. A numerical example demonstrates the effectiveness of the proposed conditions in comparison to similar approaches.

Delay-Dependent Robust Strictly Dissipative Analysis for a Class of Singular LPV Systems with Delays

2012 ◽  
Vol 490-495 ◽  
pp. 391-395
Author(s):  
Yan Tao Wang ◽  
Xin Wang ◽  
Rui Zhi Zhang ◽  
Xing Hua Zhang
Keyword(s):  
Lyapunov Functional ◽  
Matrix Inequality ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Numerical Example ◽  
Lpv Systems ◽  
Inequality Techniques ◽  
Parameter Varying ◽  
Delay Dependent

Delay-dependent robust strictly dissipative analysis for a class of singular linear parameter-varying (LPV) systems with delays is investigated in this paper. By constructing a proper Lyapunov functional and using matrix inequality techniques, a delay-dependent robust strictly dissipativity criterion for a class of singular LPV systems with delays is derived. A numerical example is presented to demonstrate the effectiveness of the proposed method.

scholarly journals Robust Filtering for Discrete-Time Linear Parameter-Varying Descriptor Systems

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1871 ◽  
Author(s):  
Carlos Rodriguez ◽  
Karina A. Barbosa ◽  
Daniel Coutinho
Keyword(s):  
Discrete Time ◽  
Filter Design ◽  
Linear Time ◽  
Estimation Error ◽  
Sufficient Conditions ◽  
Descriptor Systems ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Parameter Varying ◽  
Time Linear

This paper deals with robust state estimation for discrete-time, linear parameter varying (LPV) descriptor systems. It is assumed that all the system state-space matrices are affine functions of the uncertain parameters and both the parameters and their variations are bounded functions of time with known minimum and maximum values. First, necessary and sufficient conditions are proposed for admissibility and bounded realness for discrete linear time-varying (DLTV) descriptor systems. Next, two convex optimisation based methods are proposed for designing admissible stationary linear descriptor filters for LPV descriptor systems which ensure a prescribed upper bound on the ℓ2-induced gain from the noise signal to the estimation error regardless of model uncertainties. The proposed filter design results were based on parameter-dependent generalised Lyapunov functions, and full-order, augmented-order and reduced-order filters were considered. Numerical examples are presented to show the effectiveness of the proposed filtering scheme. In particular, the proposed approach was used to estimate the state variables of a controlled horizontal 2-DOF robotic manipulator based on noisy measurements.

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