In this paper, Cascade PI Controller-Based Robust Model Reference Adaptive Control (MRAC) of a DC-DC boost converter is presented. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while operating in continuous conduction mode (CCM). The proposed control scheme efficiently resolved complications and challenges by using features of cascade PI control loop in combination with properties of MRAC. The accuracy of the proposed control system’s ability to track the desired signals and regulate the plant process variables in the most beneficial and optimised way without delay and overshoot is verified using MATLAB/Simulink by applying comparative analysis with single PI and cascade PI controllers. Moreover, performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor, DS2004 High-Speed A/D and CP4002 Timing and Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed two times with considerably improved disturbance rejection.

In this paper, a comprehensive investigation into discretization, effective sample time selection considering delays in the system, and time and frequency domain analysis of a DC-DC buck converter, which plays a vital role in photovoltaic (PV) systems, is conducted to enhance the understanding of their dynamic behavior, optimize control algorithms, improve system efficiency, and ensure reliable power conversion in photovoltaic applications. To effectively address the non-linear behavior and enhance digital control of a buck converter by selecting the best sample time, several approaches can be employed. These include accurate modeling and identification of non-linear elements, development of advanced control algorithms that account for non-linearities, implementation of adaptive control techniques, and utilization of feedback mechanisms to compensate for deviations from linearity. By considering and mitigating the non-linear behavior, digital control systems can achieve improved accuracy, stability, and transient behavior in regulating the buck converter's output waveforms (voltage or current). The results of the study demonstrated that the trapezoidal integration method which is also known as bilinear approximation, or Tustin's approach outperformed other commonly used discretization methods, such as first-order hold (FOH), zero-order hold (ZOH), impulse response matching (impulse invariant), and matched pole-zero (MPZ) technique, in dual-domain (both time and frequency) analysis. The key finding highlighting the superiority of the bilinear approximation was its ability to achieve the closest match in the frequency domain bridging the continuous-time and discrete systems. This finding emphasizes the significance of the bilinear approach in preserving the frequency characteristics of the original continuous-time system during discretization. By employing this method, the discrete system closely approximated the behavior of its continuous-time counterpart, ensuring accurate frequency-domain representation.

In this paper, Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller based variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is presented. The proposed control scheme resolved the drawbacks of conventional P&O MPPT method associated with the use of constant perturbation size that leads to poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update best estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in P&O algorithm that characterizes the overall system learning-based real time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcome the challenges namely, complexity, computational burden, implantation cost and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The proposed control scheme is verified using MATLAB/Simulink by applying comparative analysis with PI controlled conventional P&O MPPT algorithm. Moreover, performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor board, DS2004 A/D and CP4002 Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency.

In this paper, a symmetrical pole placement Method-based Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller is presented. The proposed PR-P controller resolved the issues that are tracking repeating control input signal with zero steady-state and mitigating of 3rd order harmonic component injected into the grid associated with the use of PI controller for single-phase PV systems. Additionally, the PR-P controller has overcome the drawbacks of frequency detuning in the grid and increase in the magnitude of odd number harmonics in the system that constitute the common concerns in the implementation of conventional PR controller developed as an alternative to PI controller. Moreover, the application of an unprecedented design process based on changing notch filter dynamics with symmetrical pole placement around resonant frequency overcomes the limitations that are essentially complexity and dependency on the precisely modelled system associated with the use of various controllers such as Adaptive, Predictive and Hysteresis in grid connected PV power generation systems. The proposed PR-P controller was validated employing Photovoltaic emulator (PVE) consisting of a DC-DC Buck power converter, a maximum power point tracking (MPPT) algorithm and a full-bridge grid connected inverter designed using MATLAB/Simulink system platform. Details of the proposed controller, Photovoltaic emulator (PVE) simulations, analysis and test results were presented in the paper.

Efficient current control in boost converters is critical for electric vehicle (EV) battery charging applications, where dynamic operating conditions challenge conventional control strategies. This paper presents a novel cascaded artificial neural network (ANN) and fuzzy logic (ANFIS) controller designed to enhance current regulation in boost converters. The performance of the proposed approach is validated through comparison with single PI, cascaded PI, and single ANFIS control schemes. To improve system performance, a sensorless current estimation technique is implemented, reducing hardware dependency and enhancing robustness, while lowering system cost. Experimental evaluations demonstrate that the proposed cascaded ANFIS controller maintains consistent current levels under rapid load changes, providing improved transient response and steady-state accuracy. Specifically, the proposed method achieves a settling time of 23 ms, compared to 185 ms for single PI and 66 ms for single ANFIS control, corresponding to an 87.6% improvement over PI. In addition, overshoot is reduced from 37.25% (PI) and approximately 20% (ANFIS) to negligible levels, while a fast rise time of 3.62 ms is obtained. These improvements reduce current deviation and transient stress, contributing to more stable and reliable charging operation. Although charging time, efficiency, and battery lifetime are not directly measured, the results indicate strong potential for improved practical charging performance. The proposed approach provides valuable insights into the integration of intelligent control methods in power electronics and supports the development of high-performance EV charging systems.

This paper provides a thorough comparative analysis of discretization techniques commonly utilized in digital control applications for DC-DC boost converters (DBCs). Given the crucial role of DC-DC converters in various industries such as renewable energy systems, electric vehicles, and portable electronic devices, it is imperative to optimize their performance through efficient digital control. This study aims to improve the understanding of the effects of discretization methods on control system behaviour. It investigates their impact on the performance, stability and accuracy of control algorithms in the context of DBC, using dSPACE real-time interface (RTI) and hardware-in-the-loop (HIL) simulation for validation. This approach replicates real-world conditions, allowing performance to be evaluated in a controlled environment. The analysis examines behaviour in the time and frequency domains, providing insight into the strengths and weaknesses of each method. Experimental validation using MATLAB/Simulink/Stateflow on dSPACE RTI 1007 processor, DS2004 high-speed A/D and CP4002 timing and digital I/O boards ensures that the comparative analysis provides practical benefits for DBC digital control applications.