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Reduced Modelling of Transmission Line Circuits using a Novel Nonlinearity Aware TPWL with Adaptive Sampling

Mathematical modelling of physical systems results into large order dynamical system. Such systems are computationally heavy to simulate. It is even difficult to design controller for such systems. To overcome such problems model order reduction of large order dynamical systems is performed. Model order reduction not only reduces computational burden but also makes control feasible. Nonlinearity aware trajectory piecewise linear technique is one of the model order reduction techniques that is used for reduction of nonlinear systems. This method is an improvement to the trajectory piecewise linear approximation. This paper adds another feature to nonlinearity aware trajectory piecewise linear approximation that further enhances its performance and produces approximations with better accuracy and much less number of sub-models thereby reducing the online computation cost. This modified algorithm is applied to a large order transmission line circuit with different nonlinearity cases and reduced models are obtained. A comparison between the simulation results obtained from the nonlinearity aware trajectory piecewise linear approximation with adaptive sampling, nonlinearity aware trajectory piecewise linear approximation and trajectory piecewise linear approximation are also shown in this paper.