Subspace Identification of Linear Time-Periodic Systems With Periodic Inputs

This letter proposes a new methodology for subspace identification of linear time-periodic (LTP) systems with periodic inputs. This method overcomes the issues related to the computation of frequency response of LTP systems by utilizing the frequency response of the time-lifted system with linear time-invariant structure instead. The response is estimated with an ensemble of input-output data with periodic inputs. This allows the frequency-domain subspace identification technique to be extended to LTP systems. The time-aliased periodic impulse response can then be estimated and the order-revealing decomposition of the block-Hankel matrix is formulated. The consistency of the proposed method is proved under mild noise assumptions. Numerical simulation shows that the proposed method performs better than multiple widely-used time-domain subspace identification methods when an ensemble of periodic data is available.

[1]  Patrizio Colaneri,et al.  Invariant representations of discrete-time periodic systems , 2000, Autom..

[2]  Michel Verhaegen,et al.  A class of subspace model identification algorithms to identify periodically and arbitrarily time-varying systems , 1995, Autom..

[3]  B. Moor,et al.  Subspace identification for linear systems , 1996 .

[4]  Patrick Guillaume,et al.  On the Advantages of Periodic Excitation in System Identification , 1994 .

[5]  Matthew S. Allen,et al.  System Identification of Dynamic Systems With Cubic Nonlinearities Using Linear Time-Periodic Approximations , 2009 .

[6]  E. Mollerstedt,et al.  Out of control because of harmonics-an analysis of the harmonic response of an inverter locomotive , 2000, IEEE Control Systems.

[7]  Lennart Ljung,et al.  Subspace-based identification of infinite-dimensional multivariable systems from frequency-response data , 1996, Autom..

[8]  Michel Verhaegen,et al.  Subspace identification of MIMO LPV systems using a periodic scheduling sequence , 2007, Autom..

[9]  Rik Pintelon,et al.  Continuous time frequency domain LPV state space identification via periodic time-varying input-output modeling , 2014, 53rd IEEE Conference on Decision and Control.

[10]  Pb Pepijn Cox Towards efficient identification of linear parameter-varying state-space models , 2018 .

[11]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[12]  Noah J. Cowan,et al.  Frequency-Domain Subspace Identification of Linear Time-Periodic (LTP) Systems , 2019, IEEE Transactions on Automatic Control.

[13]  S. Bittanti,et al.  Periodic Systems: Filtering and Control , 2008 .

[14]  Johan Schoukens,et al.  Optimized Excitation Signals for MIMO Frequency Response Function Measurements , 2005, IEEE Transactions on Instrumentation and Measurement.

[15]  Edward Tunstel,et al.  A bounded switching approach for identification of switched MIMO systems , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[16]  Tony A. Wood,et al.  Modeling, Identification, Estimation and Adaptation for the Control of Power-Generating Kites , 2018 .

[17]  J. J. Hench A technique for the identification of linear periodic state-space models , 1995 .

[18]  Annika Eichler,et al.  Automated classification and identification procedure for prediction of energy consumption in multi-mode buildings , 2017 .

[19]  Norman M. Wereley,et al.  Analysis and control of linear periodically time varying systems , 1990 .

[20]  Carlos E. S. Cesnik,et al.  System Identification Technique for Active Helicopter Rotors , 2005 .

[21]  Robert H. Halstead,et al.  Matrix Computations , 2011, Encyclopedia of Parallel Computing.