L2-stability of hinging hyperplane models via integral quadratic constraints

نویسندگان

  • Gianni Bianchini
  • Simone Paoletti
  • Antonio Vicino
چکیده

This paper is concerned with L2-stability analysis of hinging hyperplane autoregressive models with exogenous inputs (HHARX). The proposed approach relies on analysis results for systems with repeated nonlinearities based on the use of integral quadratic constraints. An equivalent linear fractional representation of HHARX models is firstly derived. In this representation, an HHARX model is seen as the feedback interconnection of a linear system and a diagonal static block with repeated scalar nonlinearity. This makes it possible to exploit the aforementioned analysis results. The corresponding sufficient condition for L2-stability can be checked via a linear matrix inequality. A numerical example shows that the proposed approach is effective in practice.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

IQC-based L2-control of linear periodic systems

Stability analysis of linear periodically time-varying systems via integral quadratic constraints is extended to the problem of control design. A full-state feedback controller that satis5es exponential stability and L2-gain disturbance attenuation from an external disturbance to a controlled output is designed for linear systems with periodically time-dependent system matrices. The main result...

متن کامل

Exponential Stability Analysis via Integral Quadratic Constraints

The theory of integral quadratic constraints (IQCs) allows verification of stability and gain-bound properties of systems containing nonlinear or uncertain elements. Gain bounds often imply exponential stability, but it can be challenging to compute useful numerical bounds on the exponential decay rate. This work presents a generalization of the classical IQC results of Megretski and Rantzer [1...

متن کامل

Hinging Hyperplanes for Non-Linear Identi cation

The hinging hyperplane method is an elegant and eecient way of identifying piecewise linear models based on the data collected from an unknown linear or nonlinear system. This approach provides \a powerful and eecient alternative to neural networks with computing times several orders of magnitude less than tting neural networks with a comparable number of parameters", as stated in 3]. In this r...

متن کامل

Support vector regression with random output variable and probabilistic constraints

Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

متن کامل

Stability Analysis of Discrete-Time Systems with Time-Varying Delays via Integral Quadratic Constraints

This manuscript presents certain l2-gain properties of and the integral quadratic constraint characterizations derived from these properties for the discrete-time time-varying operator. These IQC characterizations are crucial for the IQC analysis to be applied to study robustness of discretetime systems in the presence of time-varying delays. One new contribution of this manuscript is to utiliz...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008