The Single-Stage Grid-Connected Solar Photovoltaic (SSGC-SPV) topology has recently gained significant attention, as it offers promising advantages in terms of reducing overall losses and installation costs. We provide a comprehensive overview of the system components, which include the photovoltaic generator, the inverter, the Incremental Conductance Maximum Power Point Tracking (IC-MPPT) algorithm, and the PI regulator for DC bus voltage control. Moreover, this study presents detailed system configurations and control schemes for two types of inverters: 2L$-$3PVSI and 3L$-$3PNPC. In order to perform a comparative study between the two structures, we subjected them to the same irradiation profile using the same grid configuration. The Photovoltaic Array (PVA) irradiance is increased instantaneously, in 0.2 s, from 400 W/m² to 800 W/m², is kept at 800 W/m² for 0.2 s, is then gradually decreased from 800 W/m² to 200 W/m² in 0.2 s, is then kept at 200 W/m² for 0.2 s, and is then finally increased to 1000 W/m² for 0.2 s. We explain the operational principles of these inverters and describe the various switching states involved in generating output voltages. To achieve effective control, we adopt the Finite Set–Model Predictive Control (FS-MPC) algorithm, due to the benefits of excellent dynamic responsiveness and precise current tracking abilities. This algorithm aims to minimise the cost function, while taking into account the dynamic behaviour of both the PV system and the inverter, including any associated delays. To evaluate the performance of the FS-MPC controller, we compare its application in the three-level inverter configuration with the two-level inverter setup. The DC bus voltage is maintained at 615 V using the PI controller. The objective is to achieve a Total Harmonic Distortion (THD) below 5%, with reference to the IEEE standards. The 2L$-$3PVSI inverter is above the threshold at an irradiance of 200 W/m². The 3L$-$3PNPC inverter offers a great THD percentage, meaning improved quality of the power returned to the grid.

In this paper, an observer-based state feedback control strategy for trajectory tracking of a magnetic microrobot navigating within a 3D blood vessel is proposed. The desired trajectory to be followed by the microrobot is generated by an operator using a joystick device. To deal with the significant effect of both external disturbances and parametric uncertainties, often encountered in biological environments, a state feedback stabilization, that enforces the output tracking despite any environmental disturbances, is developed. Then, for the purpose of implementation, a state observer is developed to recover the whole state from the measured position of the microrobot. The state feedback and observer gains are determined separately by solving a set of linear matrix inequalities derived in the framework of Lyapunov stability theory. Simulation runs are performed to demonstrate the performance of the proposed control strategy.

In this paper, a control law that enforces an output tracking of a fractional diffusion process is developed. The dynamical behavior of the process is described by a space-fractional parabolic equation. The objective is to force a spatial weighted average output to track its specified output by manipulating a control variable assumed to be distributed in the spatial domain. The state feedback is designed in the framework of geometric control using the notion of the characteristic index. Then, under the assumption that the fractional diffusion process is a minimum phase system, it is shown that the developed control law guarantees exponential stability in \(L_2\)-norm for the resulting closed loop system. Numerical simulations are performed to show the tracking and disturbance rejection capabilities of the developed controller.

Trajectory tracking of microrobots presents a significant challenge in biomedical research applications such as drug delivery and artery unclogging. Microrobots are inherently subject to uncertainties and unmodeled dynamics, complicating their control. Additionally, the overheating of coils in the electromagnetic actuation system can limit controller performance. In this paper, we propose an observer-based optimal control strategy for microrobots, where the desired trajectory is generated online by means of a joystick. The control law addresses the problem of coils overheating by minimizing energy consumption while achieving trajectory tracking despite uncertainties and unmodeled dynamics. For practical implementation, we introduce a modified nonlinear extended state observer to estimate the entire state of the microrobot. Analytical tuning approaches for the control law and observer are developed using D-pole placement technique and Kharitonov’s theorem. This solution is an alternative to the use of cooling systems, which require more energy consummation and often reduce the performance of the controller. The tracking performance of the proposed control strategy is evaluated through simulation and experimental tests on a dedicated platform. Both simulation and practical results demonstrate the effectiveness of the developed control strategy.