Performance estimation of switched linear systems via n×(n+2) generalized coordinate transformations

For a continuous‐time switched linear system, the spectral abscissa, that is, the maximum Lyapunov exponent, essentially characterizes the worst‐case asymptotic divergence or convergence rate under arbitrary switching. In this study, based on the n×(n+2)$$ n\times \left(n+2\right) $$ generalized coordinate transformation method, a computational algorithm is proposed to get the performance estimation of the switched linear system under arbitrary switching by estimating the spectral abscissa of the system. Simulation examples are presented to illustrate the effectiveness of the proposed scheme, which gives a better estimation of the spectral abscissa than the existing results.