Abstract The stabilizing random early detection (RED) congestion control algorithm in transmission control protocol (TCP)/IP networks is a control theory problem. Significant attention has been drawn to this problem in the networking and control theory research communities. In this paper, we use a nonlinear dynamic model of the TCP RED congestion control algorithm to analyze and design active queue management (AQM) control systems. A linearized model of RED behavior around its nominal operating point which implicitly includes the delay in the control signal is derived. It is assumed that the system model is corrupted at the input and output by zero mean white Gaussian noise signals. An optimal state feedback stochastic controller is designed for the linearized model of the system in conjunction with a Kalman filter for state estimation. To illustrate the proposed design methodology, simulations results are presented and discussed. The proposed stochastic controller is applied to the nonlinear model of the system; Simulation results indicate that the proposed controller keeps the queue length bounded in an appropriate stochastic sense. Copyright © 2009 John Wiley & Sons, Ltd.

Hierarchical control theory is applied to the problem of management of passengers and luggage in an airport terminal. For this purpose, the airport system is analyzed and a mathematical model representing the dynamics of the controlled sections is proposed. A well-known interaction prediction method is utilized to achieve optimal performance of the system through the minimization of the queue lengths and hence the waiting time of passengers. Simulation results from a case study of Cairo Airport are presented and discussed.>

A quantitative framework to the problem of management for optimal utilization in water resources systems is developed using a dynamic Leontief modeling approach. The framework is comprised of a supply-demand disequilibrium model which allows for excess demand or supply to exist at any time. A linear control regulator formulation is undertaken in which the weighted difference between the time rate of change of actual water levels and the excess water demand is used as the control instrument. Application to the River Nile system is performed using the presently available data bank information. Several computer experiments illustrate the validity of the modeling approach and its suitability as a planning tool.

A method is developed for providing the optimal feedback gain matrix for high-order linear quadratic problems by a decentralized computational procedure. All the calculations in this approach are done off-line. The resulting gains are optimal for all initial conditions so that the eventual on-line computation is minimal. The method is applicable to both the regulator and the servomechanism problems and is particularly attractive to use for the infinite time case where even the off-line computation is small. A 22nd-order numerical example is used to illustrate the approach. The system here is the practical one of river pollution control based on some data from the river Cam near Cambridge, England. For this case, the optimal feedback matrix is calculated using the new approach.