Multi active bridge (MAB) DC-DC converters have attracted significant research attention in power conversion applications within DC microgrids, medium voltage DC and high voltage DC transmission systems. This is encouraged by MAB's several functionalities such as DC voltage stepping/matching, bidirectional power flow regulation and DC fault isolation. In that sense this family of DC-DC converters is similar to AC transformers in AC grids and are hence called DC transformers. However, DC transformers are generally less efficient compared to AC transformers, due to the introduction of power electronics. Moreover, the control scheme design is challenging in DC transformers, due to its nonlinear characteristics and multi degrees of freedom introduced by the phase shift control technique of the converter bridges. The main purpose of this research is to devise control techniques that enhance the conversion efficiency of DC transformers via the minimisation of current stresses. This is achieved by designing two generalised controllers that minimise current stresses in MAB DC transformers. The first controller is for a dual active bridge (DAB). This is the simplest form of MAB, where particle swarm optimisation (PSO) is implemented offline to obtain optimal triple phase shift (TPS) parameters, for minimising the RMS current. This is achieved by applying PSO on DAB steady-state model, with generic per unit expressions of converter AC RMS current and transferred power under all possible switching modes. Analysing the generic data pool generated by the offline PSO algorithm enabled the design of a generic real-time closed-loop PI-based controller. The proposed control scheme achieves bidirectional active power regulation in DAB over the 1 to -1 pu power range with minimum-RMS-current for buck/boost/unity modes, without the need for online optimisation or memory-consuming look-up tables. Extending the same controller design procedure for MAB was deemed not feasible, as it would involve a highly complex PSO exercise that is difficult to generalise for N number of bridges; it would therefore generate a massive data pool that would be quite cumbersome to analyse and generalise. For this reason, a second controller is developed for MAB converter without using a converter-based model, where current stress is minimised and active power is regulated. This is achieved through a new real-time minimum-current point-tracking (MCPT) algorithm, which realises iterative-based optimisation search using adaptive-step perturb and observe (P&O) method. Active power is regulated in each converter bridge using a new power decoupler algorithm. The proposed controller is generalised to MAB regardless of the number of ports, power level and values of DC voltage ratios between the different ports. Therefore, it does not require an extensive look-up table for implementation, the need for complex non-linear converter modelling and it is not circuit parameter-dependent. The main disadvantages of this proposed controller are the slightly slow transient response and the number of sensors it requires.