Optimized Nonlinear Integral Backstepping Controller for DC–DC Three-Level Boost Converters

Abstract

Multi-level DC-DC converters have been widely used in automotive and other high-power applications. Thus, the control of these text multi-level converters is an emerging thematic in power electronics to ensure their proper functioning. This paper provides a novel nonlinear control of a text DC-DC three level boost converter (T-LBC) based on a backstepping (BS) technique with an integral action and is optimized using genetic algorithms (GA). Firstly, the average state model of the text T-LBC is described. Then, this model is used to design an integral BS controller; nevertheless, the controller parameters are often determined manually, which may degrade the control quality. A genetic algorithm-based optimization method is applied to establish the best controller gains and improve the proposed controller efficiency. The asymptotic stability converter is verified using the Lyapunov method criteria. In order to validate the introduced controller under different scenarios, the Matlab/Simulink environment is used. In addition, it is compared with different controllers such as conventional backstepping, fuzzy logic, and proportional–integral–derivate (PID) controllers under varying references to highlight its performance further. Finally, the designed controller is verified experimentally by implementing it using a dSPACE 1104 control board. The simulation and experimental results show that the optimized integral BS controller presents the best performances in terms of settling time, overshoot and steady-state error.

Keywords

• Three level boost DC-DC converter
• nonlinear control
• integral backstepping
• genetic algorithms
• tuning