In this research, a new single-phase direct AC-to-AC converter, operating in buck and boost mode, with a bipolar voltage gain, is proposed. The operation is accomplished through high frequency direct and indirect PWM control of a single switch with low voltage stresses. This reduces, not only the control effort, but also the switching losses. The low voltage stresses across the high frequency switches, reduce the dv/dt problem significantly without any loss and bulky voltage snubber arrangement. The operation, in its all-operating modes, has a low inductor ripple current and switching current. The proposed converter may be employed as an AC voltage restorer in a power distribution system to cope with the voltage sag and swell issues. The detailed analysis of the proposed converter is carried out in order to compare its performance with the existing converters. The simulation results obtained using the MATLAB/Simulink environment are verified through experimental results.

This paper presents an intelligent voltage controller designed on the basis of an adaptive neuro-fuzzy inference system (ANFIS) for a flyback converter (FC) working in continuous conduction mode (CCM). The union of fuzzy logic (FL) and adaptive neural networks (ANN) makes ANFIS more robust against model parameters’ uncertainties and perturbations in input voltage or load current. ANFIS inherits the advantages of structured knowledge representation from FL and learning capability from NN. Comparative analysis showed that the ANFIS controller offers not only the superior transient response characteristics, but also excellent steady-state characteristics compared to those of the FL controller (FLC) and proportional–integral–derivative (PID) controllers, thus validating its superiority over these traditional controllers. For this purpose, MATLAB/Simulink environment-based simulation results are presented for validation of the proposed converter compensated system under all operating conditions.

Most of the traditional PID tuning methods are heuristic in nature. The heuristic approach-based tuned PID controllers show only nominal performance. In addition, in the case of a digital redesign approach, mapping of the heuristically-designed continuous-time PID controllers into discrete-time PID controllers and in case of the direct digital design approach, mapping of the continuous-time plant (forward converter) into the discrete-time plant, results in frequency distortion (or warping). Besides this, nonlinear elements such as ADC and DAC, and delay in the digital control loop deteriorate the control performance. There is a need to tune conventionally-designed digital controllers to enhance performance. This paper proposes optimized discrete-time PID controllers for a forward DC–DC converter operating in continuous conduction mode (CCM). The considered conventional digital PID controllers designed on the basis of the digital redesign and direct digital approaches are tuned by one of the multivariable unconstrained pattern search methods named Hooke–Jeeves (H–J) search method to ensure excellent output voltage regulation performance against the changes in input voltage and load current. Numerical results show that the H–J-based optimized PID compensated forward converter system shows tremendous improvement in performance compared to its unoptimized counterpart and simulated annealing (SA)-based compensated system, thus justifying the applicability of the H–J method for enhancing the performance.

In this paper, a nonlinear least squares optimization method is employed to optimize the performance of pole-zero-cancellation (PZC)-based digital controllers applied to a switching converter. An extensively used step-down converter operating at 1000 kHz is considered as a plant. In the PZC technique, the adverse effect of the (unwanted) poles of the buck converter power stage is diminished by the complex or real zeros of the compensator. Various combinations of the placement of the compensator zeros and poles can be considered. The compensator zeros and poles are nominally/roughly placed while attempting to cancel the converter poles. Although PZC techniques exhibit satisfactory performance to some extent, there is still room for improvement of the controller performance by readjusting its poles and zeros. The (nominal) digital controller coefficients thus obtained through PZC techniques are retuned intelligently through a nonlinear least squares (NLS) method using the Levenberg-Marquardt (LM) algorithm to ameliorate the static and dynamic performance while minimizing the sum of squares of the error in a quicker way. Effects of nonlinear components such as delay, ADC/DAC quantization error, and so forth contained in the digital control loop on performance and loop stability are also investigated. In order to validate the effectiveness of the optimized PZC techniques and show their supremacy over the traditional PZC techniques and the ones optimized by genetic algorithms (GAs), simulation results based on a MATLAB/Simulink environment are provided. For experimental validation, rapid hardware-in-the-loop (HiL) implementation of the compensated buck converter system is also performed.