This article presents a comprehensive review of current Magnetic Imaging Techniques (MIT), specifically Magnetic Particle Imaging (MPI) and Magnetic Resonance Imaging (MRI) methods as well as their impacts and potential in biomedical applications.The paper particularly focuses on several perspectives of MPI and MRI techniques including technical considerations, advantages, limitations, applications, future trends. Surprisingly, there are not many review articles that focused on MPI and MRI. This review will give a complete overview of present technology, perspectives, and potential future developments for MPI and MRI. MIT has become an essential and integral part of medical diagnosis in many large medical clinics and hospitals. This area is rapidly developing and evolving to meet the huge demands in medical diagnosis and prevention. MPI and MRI are promising technologies that provide reliable and effective diagnosis for many diseases including cancer. MIT uses non-invasive scanning to obtain a detailed image of the body's tissues or organs without the necessity for surgery. These techniques allow us to detect symptoms of serious diseases at an early stage. Early detection also gives patients the chance to get the right care before their illnesses advance to a late, incurable stage, potentially saving many lives.

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This work presents a control scheme to control a grid-connected single-phase photovoltaic (PV) system. The considered system has four 250 W solar panels, a non-inverting buck-boost DC-DC converter, and a DC-AC inverter with an inductor-capacitor-inductor (LCL) filter. The control system aims to track and operate at the maximum power point (MPP) of the PV panels, regulate the voltage of the DC link, and supply the grid with a unity power factor. To achieve these goals, the proposed control system consists of three parts: an MPP tracking controller module with a fuzzy-based modified incremental conductance (INC) algorithm, a DC-link voltage regulator with a hybrid fuzzy proportional-integral (PI) controller, and a current controller module using a linear quadratic regulator (LQR) for grid-connected power. Based on fuzzy control and an LQR, this work introduces a full control solution for grid-connected single-phase PV systems. The key novelty of this research is to analyze and prove that the newly proposed method is more successful in numerous aspects by comparing and evaluating previous and present control methods. The designed control system settles quickly, which is critical for output stability. In addition, as compared to the backstepping approach used in our past study, the LQR technique is more resistant to sudden changes and disturbances. Furthermore, the backstepping method produces a larger overshoot, which has a detrimental impact on efficiency. Simulation findings under various weather conditions were compared to theoretical ones to indicate that the system can deal with variations in weather parameters.

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