“…In a large-signal sense, numerous nonlinear strategies such as feedback-linearisation technique [9,10], sliding-mode control method [11,12], backstepping control technique [13,14], combination of sliding-mode with backstepping control [15], model predictive control [16,17], the fuzzy method [18], the combination of fuzzy with model predictive control [19], deep reinforcement learning method [20], passivity-based control [21] have been conducted to minimise destabilisation effects of CPLs on the DC microgrids. It can be observed that the represented schemes [9][10][11][12][13][14][15][16][17][18][19][20][21] stabilise the entire power system with an asymptotical convergence rate in infinite time, which may not be adequate for abrupt changes in various system operating states and stepwise load variations. One way of overcoming this challenge is to establish a finite-time control strategy, which not only accelerates the converging speed but also provides strong robustness in the face of uncertainties, and improves disturbance attenuation.…”