In this work, we present a physics-based model for a two-dimensional electron gas (2-DEG) density at heterointerface in AlGaN/GaN high electron mobility transistor (HEMT). One-dimensional Schrödinger-Poisson equations are solved self-consistently using a nonuniform mesh within the framework of the nextnano device simulation software. The 2-DEG density of AlGaN/GaN HEMT is investigated through the dependence of electron concentrations on various structural parameters such as barrier layer thickness, doping concentration, and the Al content. We report calculations of gate capacitance from charge density characteristics with respect to gate voltage. Good agreement between calculation and experiment is found.

This paper focuses on the modelling and control of an electromagnetic suspension using the bond graph tool. This technique combines graphical and relational aspects to establish connections between bond graph elements, particularly in deducing junction relationships and employing bicausal inversion for trajectory tracking controller design. To determine the controller parameters, we utilized a meta-heuristic method called Firefly for optimization, thus avoiding the need for trial and error. The simulation was conducted using 20-Sim software and a Matlab/Simulink script, which yielded improved results. This paper presents an initial contribution that demonstrates the integration of meta-heuristic optimization and the bond graph tool for parameter selection in 20-sim simulation software.

The outcomes of this research significantly contribute to the existing body of knowledge on metaheuristic optimization techniques for active suspension systems. By conducting thorough investigations and analyses, the study effectively demonstrates the remarkable advantages of the Firefly algorithm in optimizing the performance of both conventional and intelligent controllers for active suspension systems. These findings highlight the algorithm's potential to revolutionize the field and pave the way for more efficient and robust control strategies. The demonstrated effectiveness of the Firefly algorithm in minimizing the error between the car's displacements and the disturbances of the road is particularly noteworthy. This achievement ensures a more precise and accurate tracking of the desired trajectory, regardless of the input signal used, whether it be an impulse, sine wave, or step-wise graded signal.