Abstract:- This paper introduces a technique for modeling and effectively controlling the trajectory tracking of a robotic manipulator through an LQG controller optimized by the IPSO algorithm. Extensive simulations have been conducted within the MATLAB simulation environment. The LQG, which combines a Kalman Filter (KF) and a Linear Quadratic Regulator (LQR), is developed to follow the desired input for the robotic manipulator while minimizing the impact of process and measurement noise on its performance. The parameters of the LQG controller, which include the elements of the state and control weighting matrices for the LQR and KF, are optimally adjusted using the IPSO method. The validation of the proposed hybrid LQG-IPSO controller is conducted based on the control criteria parameters. The findings demonstrate that the proposed hybrid LQGIPSO controller can achieve excellent movement performance. To fully leverage the capabilities of the IPSO algorithm, careful adjustment and determination of IPSO parameters such as inertia weight, iteration count, acceleration constants, and particle quantity are essential. Therefore, The initial focus of this study is to conduct a comparative analysis of various fitness functions; simulation results indicate that the proposed hybrid LQGIPSO control method achieves commendable fitness outcomes with minimal steady-state error (ess). Following this, a comparison of the performances of a robotic manipulator using the hybrid LQG-IPSO controller, hybrid LQR-IPSO controller, LQG controller, and LQR controller is also presented. Based on the analysis, it can be concluded that superior performance parameters are attained with the hybrid LQG-IPSO controller when compared to its counterparts—the hybrid LQR-IPSO controller, LQG controller, and LQR controller—offering enhanced performance.

Keyw Keywords: Linear Quadratic Gaussian (LQG) controller, Linear Quadratic Regulator (LQR) controller, Improved Particle Swarm Optimization (IPSO) algorithm, Particle Swarm Optimization (PSO) algorithm and MATLAB etc

With the growing demand for fast and reliable telecommunications infrastructure, deploying a Long-Term Evolution (LTE) network has become a necessity to support both economic and social development. This paper presents three proposed layouts for designing an LTE network in the downtown area of Gharyan, which represents the city’s central and most densely populated zone. The project was motivated by the uneven distribution of coverage across the area, whereseveral locations experience either a complete lack of service or very weak signal reception. The aim is to support the city’s digital transformation by improving access to mobile internet and data services, which in turn enhances business performance, emergency response, public service efficiency, education, remote learning, telemedicine, and remote work opportunities. To implement this plan, the design process relied on Mentum Planet software, a tool specialized in mobile network planning, using real-world terrain and signal data provided by Almadar Company. Three different network layout designs were simulated using two built-in propagation models: the Planet General Model (PGM) and the Q9 model. These simulations were conducted to assess signal strength and coverage across the study area. The analysis showed that one of the layouts provided significantly better signal quality and broader coverage compared to the others. Moreover, the Q9 model proved more reliable in predicting signal behavior in densely built urban settings. Based on these findings, a set of technical recommendations has been developed to guide the future implementation of LTE networks in similar environments, while also addressing challenges such as terrain variations, signal interference, and infrastructurelimitations. In conclusion, this work contributes to enhancing telecommunications services in Gharyan and supports broader efforts toward innovation and digital inclusion across key sectors in the region.