Exploiting Structure in MIMO Scaled Graph Analysis
Scaled graphs offer a graphical tool for analysis of nonlinear feedback systems. Although recently substantial progress has been made in scaled graph analysis, at present their use in multivariable feedback systems is limited by conservatism. In this paper, we aim to reduce this conservatism by introducing multipliers and exploit system structure in the analysis with scaled graphs. In particular, we use weighted inner products to arrive at a weighted scaled graph and combine this with a commutation property to formulate a stability result for multivariable feedback systems. We present a method for computing the weighted scaled graph of Lur'e systems based on solving sets of linear matrix inequalities, and demonstrate a significant reduction in conservatism through an example.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Graphical Dominance Analysis for Linear Systems: A Frequency-Domain Approach
We propose a frequency-domain approach to dominance analysis for multi-input multi-output (MIMO) linear time-invariant systems. The dominance of a MIMO system is defined to be the number of its poles in the open right ha…
Stability results for MIMO LTI systems via Scaled Relative Graphs
This paper proposes a new approach for stability analysis of multi-input, multi-output (MIMO) feedback systems through Scaled Relative Graphs (SRGs). Unlike traditional methods, such as the Generalized Nyquist Criterion …
Deep Learning Framework for Hybrid Analog-Digital Signal Processing in mmWave Massive-MIMO Systems
Hybrid analog-digital signal processing (HSP) is an enabling technology to harvest the potential of millimeter-wave (mmWave) massive-MIMO communications. In this paper, we present a general deep learning (DL) framework f…
SALSA: A Sequential Alternating Least Squares Approximation Method For MIMO Channel Estimation
In this paper, we consider the channel estimation problem in sub-6 GHz uplink wideband MIMO-OFDM communication systems, where a user equipment with a fully-digital beamforming structure is communicating with a base stati…
Improving CSI-based Massive MIMO Indoor Positioning using Convolutional Neural Network
Multiple-input multiple-output (MIMO) is an enabling technology to meet the growing demand for faster and more reliable communications in wireless networks with a large number of terminals, but it can also be applied for…
Position