In recent years, DC-DC power converters have been used in several applications like switched mode power supplies, wind energy conversion systems, PV arrays for maximising the energy harvests as well as in integrating the energy storage systems with smart power grids.[1-4]. The control methodologies for DC-DC converter are designed for tight regulation of output voltage amidst varying input and loading conditions, keeping in mind the unpredictable nature of such diverse plants. Traditional linear control schemes for power converters are designed based on their mathematical models. Mathematical modelling is an efficient tool to analyse the static and dynamic characteristics of any system. Several well-documented methods like the state space averaging method proposed by Middlebrook [5], PWM switch averaging method [6, 7] and the injected absorbed current method [8] are available in the literature to model any non-linear switched mode power converter. However, the mathematical model developed for controller design may typically have inconsistencies when compared with the actual plant. The controller should be well equipped to obtain optimized performance taking into account such mismatches in the modelled system. Non-linear control techniques are well suited to deal with such discrepancies in the system [9, 10]. A variable structure non-linear control scheme like the sliding mode control acts as a perfect fit for controlling a highly non-linear and time varying system like the DC-DC switched mode converter. A DC-DC converter controlled through sliding mode theory yields large signal stability as opposed to the linear conventional controllers which guarantee desired performance against only small perturbations in input voltage or load current [11, 12]. Conventional sliding mode controller for switched mode converter however suffers from the inherent disadvantage of variable switching frequency when subjected to parameter variations. The consequence of this variable switching are increased switching losses, losses in the inductor and transformer core and electromagnetic interference issues. Furthermore, the variable switching frequency makes it difficult to design the filters in the converter system [13]. Researchers down the years have proposed numerous techniques to overcome this shortcoming by incorporating artificial intelligence based algorithms along with sliding mode control [14, 15]. However, the main problem with the application of adaptive sliding mode schemes in DC-DC converters is that its industrial implementation is impractical since it typically involves the use of costly digital signal processors. In addition to the aforementioned drawback, conventional SMC exhibits non-zero steady state error due to its proportional derivative (PD)-type feedback. The PD feedback requires a small error to produce the necessary control signal for steady state operation [16]. Through addition of an integral term to the control law, such a problem can be eliminated [17].