Improved Control Methodologies for Luo Converter

Abstract

DC-DC converters form a class of highly nonlinear systems and are widely used in newlinemost of the practical applications. Positive Output Elementary Luo Converter newline(POELC) is a fourth-order converter used to regulate dc voltages in low power newlineapplications with varying input voltage and load conditions. POELC is employed to newlineregulate dc voltages for sensitive load applications like SMPS, powering hard disks newlineetc. The control of higher-order converters is always a challenging task due to the newlinehighly nonlinear nature of these converters. Hence the development of optimized newlinecontrollers for POELC is proposed in this research work. POELC is a direct output newlinebuck-boost type converter with an additional output filter stage.Conventional controllers like Proportional Integral Controller (PIC), Fuzzy PI Controller (FPIC), Model Predictive Controller (MPC) and Linear Quadratic Regulator (LQR) are popular. In this research, the focus is towards optimizing the performance of the conventional controllers using meta-heuristic optimization algorithms and a new class of optimized controllers were proposed. The proposed control methods are investigated for transient and steady-state performances considering practical operating conditions. The sensitivity of the controllers with load disturbances are studied along with servo responses is presented. The controllers are designed, simulated and the performance of POELC with various controllers is evaluated in the MATLAB/Simulink environment. From the simulations, the PI controller exhibits better performance in the linear region whereas in the nonlinear region, it is unsatisfactory due to time variance and switching nature.Hence to enhance the performance, an intelligent FPIC technique is formulated. FPIC is capable of providing a better static and dynamic performance with relative smaller error over PI control. To achieve a competitive performance using a PI controller, its parameters are tuned using meta-heuristic algorithms like Cuckoo Search Optimization