Optimized sliding mode current controller for power converters with non-minimum phase nature

This paper proposes a unified method to design an optimized type of the hysteresis modulation-based sliding mode current controller for non-minimum phase power converters in continuous conduction mode. The traditional sliding mode controlled converters have a slow transient voltage response at heavy loads, a large overshoot at light loads and during abrupt output resistance variations. To solve these problems, an optimized feedback control scheme is used according to the output resistance to adjust the coefficients of the controller. The basic idea of this controller is to suggest a new way for reduction of the sensitivity function amplitude of the closed loop system. The presented approach is developed for three basic DC/DC converters; i.e. boost, buck-boost and quadratic boost converters. Generally, the certain advantages of the suggested control approach are: (i) a fast transient response can be achieved in heavy load conditions, (ii) the voltage overshoot can be effectively reduced during load variations; (iii) the transient voltage overshoot can be eliminated in light load conditions; (iv) the closed loop control sensitivity can be reduced and therefore, the performance specification of a control system can be improved compared with the conventional sliding mode current control. To show the reliability of the suggested control scheme, simulations and experimental results for the derived systems are developed. Several conditions are performed to confirm the effectiveness of the proposed controller.     

Optimal adaptive reset control with guaranteed transient and steady state tracking error bounds

In this paper, a solution for improvement of transient performance in adaptive control of nonlinear systems is proposed. An optimal adaptive controller based on a reset mechanism and a prescribed performance bound is devised. The suggested controller has the structure of adaptive backstepping controller in which the estimated parameters are reset to an optimal value. The designed controller ensures both the transient bound and the asymptotical convergence of the states. It is shown that the tracking error satisfies the prescribed performance bound all the time, besides the speed of the convergence rate is increased by resetting the estimated parameters. The results have been proved through both the analytical and simulation studies. The proposed method is applied to an Augmented Quarter Car Model as a case study. Simulation results verify the established theoretical consequences that the prescribed performance bound based optimal adaptive reset controller can enhance the transient performance of the adaptive controller.     

Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks

We analyze whether preferential attachment in scientific coauthorship networks is different for authors with different forms of centrality. Using a complete database for the scientific specialty of research about “steel structures,” we show that betweenness centrality of an existing node is a significantly better predictor of preferential attachment by new entrants than degree or closeness centrality. During the growth of a network, preferential attachment shifts from (local) degree centrality to betweenness centrality as a global measure. An interpretation is that supervisors of PhD projects and postdocs broker between new entrants and the already existing network, and thus become focal to preferential attachment. Because of this mediation, scholarly networks can be expected to develop differently from networks which are predicated on preferential attachment to nodes with high degree centrality.