Abstract

Trajectory piecewise linear (TPWL) approximation is a well-known model order reduction technique for non-linear systems. It involves weighted summation of the dimensionally reduced linear systems obtained at certain points on the system trajectory. The points at which the linearised systems are produced are called linearization points (LP). The LPs are important as they decide the quality and the complexity of the approximation. The criterion of selecting LPs play a crucial role as the fidelity of the reduced model depends upon it. According to the previous methods, a new linearised model is formed whenever the distance of the linear model being simulated from all the previously selected LPs is greater than some chosen distance. This distance is heuristically chosen in the conventional LP selection schemes. This article proposes a new criterion of selecting the distance and the LPs that not only removes the ambiguity but also enhances the performance of the approximation. With the proposed scheme, much smaller number of LPs are needed and the distances are computed automatically, instead of being arbitrarily selected. A number of relevant examples are presented, showing the advantages of the method, both in the number of LPs and in the error of the TPWL approximation.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.