Sistem Kendali Kongesti Di Internet

Internet Congestion Control System. Internet congestion occurs when resource demands exceeds the network capacity. But, it is not the only reason. Congestion can happen on some users because some others user has higher sending rate. Then some users with lower sending rate will experience congestion. This partial congestion is caused by inexactly feedback. At this moment congestion are solved by the involvement of two controlling mechanisms. These mechanisms are flow/congestion control in the TCP source and Active Queue Management (AQM) in the router. AQM will provide feedback to the source a kind of indication for the occurrence of the congestion in the router, whereas the source will adapt the sending rate appropriate with the feedback. These mechanisms are not enough to solve internet congestion problem completely. Therefore, this paper will explain internet congestion causes, weakness, and congestion control technique that researchers have been developed. To describe congestion system mechanisms and responses, the system will be simulated by Matlab

Designing Optimal Speed Control with Observer Using Integrated Battery-electric Vehicle (IBEV) Model for Energy Efficiency

This paper develops an optimal speed control using a linear quadratic integral (LQI) control standard with/without an observer in the system based on an integrated battery-electric vehicle (IBEV) model. The IBEV model includes the dynamics of the electric motor, longitudinal vehicle, inverter, and battery. The IBEV model has one state variable of indirectly measured and unobservable, but the system is detectable. The objectives of this study were: (a) to create a speed control that gets the exact solution for a system with one indirect measurement and unobservable state variable; and (b) to create a speed control that has the potential to make a more efficient energy system. A full state feedback LQI controller without an observer is used as a benchmark. Two output feedback LQI controllers are designed; including one controller uses an order-4 observer and the other uses an order-5 observer. The order-4 observer does not include the battery state of charge as an observer state whereas the order-5 observer is designed by making all the state variable as the observer state and using the battery state of charge as an additional system output. An electric passenger minibus for public transport with 1500 kg weight was used as the vehicle model. Simulations were performed when the vehicle moves in a flat surface with the increased speed from stationary to 60 km/h and moves according to standard NEDC driving profile. The simulation results showed that both the output feedback LQI controllers provided similar speed performance as compared to the full state feedback LQI controller. However, the output feedback LQI controller with the order-5 observer consumed less energy than with the order-4 observer, which is about 10% for NEDC driving profile and 12% for a flat surface. It can be concluded that the LQI controller with order-5 observer gives better energy efficiency than the LQI controller with order-4 observe