F. Cacace, A. Germani, C. Manes, and R. Setola, "A New Approach to the Positive Realization of Linear MIMO Systems," IEEE Trans. on Automatic Control , vol. 57, n. 1, pag. 119--134, 2012. (doi:10.1109/TAC.2011.2158170)
Browse Journals & Magazines > Automatic Control, IEEE Trans ...> Volume:57 Issue:1 Back to Results | Next » Help A New Approach to the Internally Positive Representation of Linear MIMO Systems Full text access may be available To access full text, please use your member or institutional sign in. Learn more about subscription options Already purchased? View now Forgot Username/Password? Forgot Institutional Username or Password? Athens/Shibboleth This paper appears in: Automatic Control, IEEE Transactions on Date of Publication: Jan. 2012 Author(s): Cacace, F. Univ. Campus Bio-Medico di Roma, Rome, Italy Germani, A. ; Manes, C. ; Setola, R. Volume: 57 , Issue: 1 Page(s): 119 - 134 Product Type: Journals & Magazines Available Formats Non-Member Price Member Price PDF/HTML US€ 31,00 US€ 10,00 Learn how you can qualify for the best price for the item! Download Citations Email Print Rights And Permissions Save to Project Abstract The problem of representing linear systems through combination of positive systems is relevant when signal processing schemes, such as filters, state observers, or control laws, are to be implemented using “positive” technologies, such as Charge Routing Networks and fiber optic filters. This problem, well investigated in the SISO case, can be recasted into the more general problem of Internally Positive Representation (IPR) of systems. This paper presents a methodology for the construction of such IPRs for MIMO systems, based on a suitable convex positive representation of complex vectors and matrices. The stability properties of the IPRs are investigated in depth, achieving the important result that any stable system admits a stable IPR of finite dimension. A main algorithm and three variants, all based on the proposed methodology, are presented for the construction of stable IPRs. All of them are straightforward and are characterized by a very low computational cost. The first and second may require a large state-space dimension to provide a stable IPR, while the third and the fourth are aimed to provide stable IPRs of reduced order.