The world has become more like a small community thanks to the internet, which connects millions of people,
businesses, and pieces of technology for a variety of uses. Because of the significant influence these networks have
on our lives, maintaining their efficiency is important, which necessitates addressing issues like congestion. In this
study, PI-controller gains are adjusted using a variety of optimization strategies to regulate the nonlinear TCP/AQM
model. This controller commits controlled pressured signaling characteristics and modifies computer network
congestion. First manual tune PI-Controller are used; then several optimization techniques were used to tune PIcontroller gains (Particle Swarm Optimization (PSO), Ant-Colony Optimization (ACO) and Simulated Annealing
algorithm (SA)) and then Linear Quadratic Regulator theory are used. To test the reliability and effectiveness of each
of the suggested controllers, several tests utilizing varied network parameter values, different queue sizes, and extra
disturbances were conducted. MATLAB was used for all experiments., the results show the superiority of the LQR
controller over PI controller with both manual and optimal tuning techniques.
