This paper presents an analog-digital hybrid strategy for implementing Model Predictive Control (MPC) as applied to grid-connected converters. It highlights the challenges associated with finite control set MPC (FCS-MPC) and proposes solutions to mitigate these limitations. A fair comparison between a fully digital microprocessor−based implementation and an analog-assisted digital system is also presented. To validate the proposed architecture and analyze its advantages and limitations, MPC is implemented for a grid-connected Voltage Source Converter (VSC). At each sampling instant, the MPC algorithm solves the system’s mathematical model and an optimization problem over a two-step prediction horizon to determine the optimal switching state for the subsequent time step. This work presents the possible applicability of analog-digital hybrid systems in computationally intensive real-time scenarios. It also brings out the practical challenges in the implementation of such systems.

This paper presents an analog-digital hybrid approach for implementing a digital twin estimator aimed at health monitoring of power electronic converters. The digital twin serves as a real-time virtual counterpart of the physical converter, replicating its key dynamic characteristics to enable predictive diagnostics and performance optimization. The proposed framework leverages analog-digital processing to enable direct integration with sensor outputs and parallel operation alongside the converter on the same embedded control platform. This embedded implementation facilitates adaptive control and supports real-time decision-making. The effectiveness of the proposed method is validated through its application to a DC-DC buck converter implemented on the developed analog-digital hybrid system. This work demonstrates the potential of hybrid computation for real-time health monitoring and highlights key implementation considerations for embedded analog-digital system-based digital twin systems.

This paper is on the possible uses of analog computing in the acceleration of digital implementations of real-time simulation and control in power engineering. We present a brief history of analog and hybrid computing, make the case for a renewed interest in the use of hybrid computing in power engineering, and provide practical results from a small-scale hybrid computer as applied to specific cases. We consider a hybrid computing approach in which the analog computing part consists of analog integrators, scalers and adders, and a digital processor to perform algebraic computations. The digital processor also monitors, controls and reprograms the analog part. We discuss three broad areas that potentially benefit from hybrid computing: real-time simulation, real-time optimization in the control of power electronic converters, and real-time estimators in the closed-loop control of power electronic systems.

Major progress has been made towards increasing access to education at all levels and increasing enrolment rates in schools but in order to ensure inclusive quality education for all, a new delivery method that caters to educating homebound disabled children is needed. This paper aims to study how virtual reality with telepresence robots can be used to create virtually inclusive classrooms that provide better educational opportunities for homebound students with disabilities.