Particle Swarm Optimization Based LQ-Servo Controller for Congestion Avoidance

Abstract

The network congestion is an essential problem that leads to packetslosing and performance degradation. Thus, preventing congestion in thenetwork is very important to enhance and improve the quality of service. Activequeue management (AQM) is the solution to control congestion in TCP networkmiddle nodes to improve theire performance. We design a linear quadratic(LQ)-servo controller as an AQM applied to TCP network to control congestionand attempt to achieve high quality of service under dynamic networkenvironments. The LQ-servo controller is proposed to provide queue lengthstabilization with a small delay and faster settling time. The designed controllerparameters are tuned by using the particle swarm optimization (PSO) method.The PSO algorithm was fundamentally applied to find the optimal controllerparameters Q and R, such that a good output response could be obtained. The PIcontroller is examined for comparison reasons. The MATLAB simulation resultshows that the controller is more effective than the PI in reaching zero steadystateerror with better congestion avoidance under the dynamic networkenvironment. Moreover, the proposed controller achieves a smaller delay andfaster settling time.